perf(core): streamline entity write upserts

Signed-off-by: phernandez <paul@basicmachines.co>

.github/workflows/test.yml

@@ -6,7 +6,6 @@ concurrency:
 
 on:
   push:
-    branches: [ "main" ]
   pull_request:
     branches: [ "main" ]
 
@@ -52,7 +51,6 @@ jobs:
   test-sqlite-unit:
     name: Test SQLite Unit (${{ matrix.os }}, Python ${{ matrix.python-version }})
     timeout-minutes: 30
-    needs: [static-checks]
     strategy:
       fail-fast: false
       matrix:
@@ -92,14 +90,13 @@ jobs:
         run: |
           uv pip install -e ".[dev]"
 
-      - name: Run tests (SQLite Unit)
+      - name: Run tests
         run: |
           just test-unit-sqlite
 
   test-sqlite-integration:
     name: Test SQLite Integration (${{ matrix.os }}, Python ${{ matrix.python-version }})
     timeout-minutes: 45
-    needs: [static-checks]
     strategy:
       fail-fast: false
       matrix:
@@ -139,21 +136,37 @@ jobs:
         run: |
           uv pip install -e ".[dev]"
 
-      - name: Run tests (SQLite Integration)
+      - name: Run tests
         run: |
           just test-int-sqlite
 
   test-postgres-unit:
     name: Test Postgres Unit (Python ${{ matrix.python-version }})
     timeout-minutes: 30
-    needs: [static-checks]
     strategy:
       fail-fast: false
       matrix:
-        python-version: [ "3.12", "3.13", "3.14" ]
+        include:
+          - python-version: "3.12"
+          - python-version: "3.13"
+          - python-version: "3.14"
     runs-on: ubuntu-latest
-
-    # Note: No services section needed - testcontainers handles Postgres in Docker
+    services:
+      postgres:
+        image: pgvector/pgvector:pg16
+        env:
+          POSTGRES_USER: basic_memory_user
+          POSTGRES_PASSWORD: dev_password
+          POSTGRES_DB: basic_memory_test
+        ports:
+          - 5432:5432
+        options: >-
+          --health-cmd "pg_isready -U basic_memory_user -d basic_memory_test"
+          --health-interval 10s
+          --health-timeout 5s
+          --health-retries 5
+    env:
+      BASIC_MEMORY_TEST_POSTGRES_URL: postgresql://basic_memory_user:dev_password@127.0.0.1:5432/basic_memory_test
 
     steps:
       - uses: actions/checkout@v4
@@ -180,21 +193,37 @@ jobs:
         run: |
           uv pip install -e ".[dev]"
 
-      - name: Run tests (Postgres Unit)
+      - name: Run tests
         run: |
           just test-unit-postgres
 
   test-postgres-integration:
     name: Test Postgres Integration (Python ${{ matrix.python-version }})
     timeout-minutes: 45
-    needs: [static-checks]
     strategy:
       fail-fast: false
       matrix:
-        python-version: [ "3.12", "3.13", "3.14" ]
+        include:
+          - python-version: "3.12"
+          - python-version: "3.13"
+          - python-version: "3.14"
     runs-on: ubuntu-latest
-
-    # Note: No services section needed - testcontainers handles Postgres in Docker
+    services:
+      postgres:
+        image: pgvector/pgvector:pg16
+        env:
+          POSTGRES_USER: basic_memory_user
+          POSTGRES_PASSWORD: dev_password
+          POSTGRES_DB: basic_memory_test
+        ports:
+          - 5432:5432
+        options: >-
+          --health-cmd "pg_isready -U basic_memory_user -d basic_memory_test"
+          --health-interval 10s
+          --health-timeout 5s
+          --health-retries 5
+    env:
+      BASIC_MEMORY_TEST_POSTGRES_URL: postgresql://basic_memory_user:dev_password@127.0.0.1:5432/basic_memory_test
 
     steps:
       - uses: actions/checkout@v4
@@ -221,14 +250,13 @@ jobs:
         run: |
           uv pip install -e ".[dev]"
 
-      - name: Run tests (Postgres Integration)
+      - name: Run tests
         run: |
           just test-int-postgres
 
   test-semantic:
     name: Test Semantic (Python 3.12)
     timeout-minutes: 45
-    needs: [static-checks]
     runs-on: ubuntu-latest
 
     steps:
@@ -256,66 +284,6 @@ jobs:
         run: |
           uv pip install -e ".[dev]"
 
-      - name: Run tests (Semantic)
+      - name: Run tests
         run: |
           just test-semantic
-
-  coverage:
-    name: Coverage Summary (combined, Python 3.12)
-    timeout-minutes: 60
-    needs:
-      - static-checks
-      - test-sqlite-unit
-      - test-sqlite-integration
-      - test-postgres-unit
-      - test-postgres-integration
-      - test-semantic
-    if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/main' }}
-    runs-on: ubuntu-latest
-
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: true
-
-      - name: Set up Python 3.12
-        uses: actions/setup-python@v4
-        with:
-          python-version: "3.12"
-          cache: "pip"
-
-      - name: Install uv
-        run: |
-          pip install uv
-
-      - uses: extractions/setup-just@v3
-
-      - name: Create virtual env
-        run: |
-          uv venv
-
-      - name: Install dependencies
-        run: |
-          uv pip install -e ".[dev]"
-
-      - name: Run combined coverage (SQLite + Postgres)
-        run: |
-          just coverage
-
-      - name: Add coverage report to job summary
-        if: always()
-        run: |
-          {
-            echo "## Coverage"
-            echo ""
-            echo '```'
-            uv run coverage report -m
-            echo '```'
-          } >> "$GITHUB_STEP_SUMMARY"
-
-      - name: Upload HTML coverage report
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: htmlcov
-          path: htmlcov/

AGENTS.md

@@ -442,5 +442,9 @@ With GitHub integration, the development workflow includes:
 3. **Branch management** - Claude can create feature branches for implementations
 4. **Documentation maintenance** - Claude can keep documentation updated as the code evolves
 5. **Code Commits**: ALWAYS sign off commits with `git commit -s`
+6. **Pull Request Titles**: PR titles must follow the semantic format enforced by `.github/workflows/pr-title.yml`: `type(scope): summary`
+   - Allowed types: `feat`, `fix`, `chore`, `docs`, `style`, `refactor`, `perf`, `test`, `build`, `ci`
+   - Allowed scopes: `core`, `cli`, `api`, `mcp`, `sync`, `ui`, `deps`, `installer`
+   - Example: `fix(cli): propagate cloud workspace routing`
 
 This level of integration represents a new paradigm in AI-human collaboration, where the AI assistant becomes a full-fledged team member rather than just a tool for generating code snippets.

CHANGELOG.md

@@ -2,13 +2,211 @@
 
 ## Unreleased
 
+## v0.20.3 (2026-03-26)
+
+### Bug Fixes
+
+- **#698**: CLI cloud commands now use API key when configured
+  - `get_authenticated_headers()` only checked OAuth tokens, ignoring `config.cloud_api_key`
+  - All CLI cloud commands (`upload`, `status`, `snapshot`, `restore`, etc.) failed for API-key-only users while MCP tools worked fine
+  - Now mirrors the same credential priority as MCP: API key first, OAuth fallback
+  - Fixes `bm cloud upload --project` returning "project does not exist" when authenticated with `bmc_*` API key
+
+## v0.20.2 (2026-03-10)
+
+### Bug Fixes
+
+- Fix auto-update Homebrew detection: `brew outdated` exits 1 when a formula is outdated, not on error
+  - Previously treated exit code 1 as a failure, causing "Automatic update check failed" instead of detecting the available update
+
+## v0.20.1 (2026-03-10)
+
+### Bug Fixes
+
+- **#661**: Fix `bm project list` MCP column to show transport type (stdio/https) instead of DB presence
+  - Renamed "MCP (stdio)" column to "MCP"
+  - Shows actual routing mode: `stdio` for local, `https` for cloud projects
+  - Clears local path display for cloud-mode projects
+- **#662**: Invalidate config cache when file is modified by another process
+  - Adds mtime-based cache validation to `ConfigManager.load_config()`
+  - Long-lived processes (MCP stdio server) now detect external config changes
+  - Fixes `bm project set-cloud` having no effect on running MCP server
+
+## v0.20.0 (2026-03-10)
+
 ### Features
 
+- **#643**: Default-on auto-update system and `bm update` command
+  - Automatic background update checks for CLI installs (uv tool, Homebrew)
+  - Install-source detection (homebrew, uv_tool, uvx, unknown) with uvx skip behavior
+  - Periodic check gating via `auto_update_last_checked_at` + `update_check_interval` config
+  - Manager-specific update flows: Homebrew (`brew upgrade`) and uv tool (`uv tool upgrade`)
+  - Silent, non-blocking MCP behavior via daemon thread before server run
+  - Manual commands: `bm update` (force check + apply) and `bm update --check` (check only)
+  - New config fields: `auto_update`, `update_check_interval`, `auto_update_last_checked_at`
+
+## v0.19.2 (2026-03-09)
+
+### Bug Fixes
+
+- **#657**: Coerce string params to list/dict in MCP tools
+  - MCP clients that serialize `list`/`dict` arguments as JSON strings no longer fail Pydantic validation
+  - Adds `BeforeValidator` coercion to `search_notes` (`entity_types`, `note_types`, `tags`, `metadata_filters`), `write_note` (`metadata`), and `canvas` (`nodes`, `edges`)
+- **#655**: Handle SQLite and Windows semantic search regressions
+  - Fix embedding status query for non-semantic SQLite databases
+  - Windows-safe log file rotation with per-process log filenames
+  - Robust `setup_logging` that handles all environments cleanly
+
+## v0.19.1 (2026-03-08)
+
+### Bug Fixes
+
+- **#649**: Enforce strict entity resolution in destructive MCP tools (`edit_note`, `move_note`, `delete_note`)
+  - Prevents fuzzy-match fallback from silently editing/moving/deleting the wrong note
+  - DST-related timeframe validation fix (round instead of truncate days)
+
+### Features
+
+- **#648**: Add `insert_before_section` and `insert_after_section` edit operations
+- Add `GET /knowledge/graph` endpoint for full graph visualization
+
+### Dependencies
+
+- Bump authlib from 1.6.6 to 1.6.7
+
+## v0.19.0 (2026-03-07)
+
+### Highlights
+
+- **Semantic vector search** for SQLite and Postgres with FastEmbed embeddings
+- **Schema system** for validating and inferring knowledge base structure
+- **Per-project cloud routing** with API key authentication
+- **Upgraded to FastMCP 3.0** with tool annotations
+- **CLI overhaul** with JSON output, workspace awareness, and project dashboard
+
+### Features
+
+- **#550**: Add semantic vector search for SQLite and Postgres
+  - FastEmbed-based embeddings with automatic backfill
+  - Hybrid search combining full-text and vector similarity
+  - Score-based fusion replacing RRF for better ranking
+  - `min_similarity` override for tuning search precision
+  - Semantic dependencies are now default, with optional extras fallback
+
+- **#549**: Schema system for Basic Memory
+  - `schema_infer` — infer schema from existing notes
+  - `schema_validate` — validate notes against a schema definition
+  - `schema_diff` — compare schemas across projects
+  - Frontmatter validation support (#597)
+  - Read schema definitions from file instead of stale DB metadata (#635)
+
+- **#555**: Per-project local/cloud routing with API key auth
+  - Individual projects route through cloud while others stay local
+  - `basic-memory cloud set-key` and `basic-memory project set-cloud/set-local`
+  - Stdio MCP honors per-project cloud routing (#590)
+
+- **#598**: Upgrade FastMCP 2.12.3 to 3.0.1 with tool annotations
+
+- **#585**: Add JSON output mode for MCP tools (default text)
+  - `--json` output for CLI commands for scripting and CI
+
+- **#576**: Add workspace selection flow for MCP and CLI
+  - Workspace-aware cloud project listing
+  - CLI refactoring for workspace support
+
+- **#544**: Project-prefixed permalinks and memory URL routing
+
+- **#632**: Add overwrite guard to `write_note` tool
+
+- **#614**: `edit_note` append/prepend auto-creates note if not found
+
+- **#609**: Richer content context in search results
+  - Return matched chunk text in search results (#601)
+  - Improved content hit rate
+
+- **#602**: Add `created_by` and `last_updated_by` user tracking to Entity
+
+- **#600**: Rename `entity_type` to `note_type` across codebase
+
+- **#574**: Add `display_name` and `is_private` to ProjectItem
+
+- **#569**: Expose `external_id` in EntityResponse and link resolver
+
+- **#567**: Isolate default SQLite DB by config dir
+
+- **#560**: Enable `default_project_mode` by default
+
+- **#559**: Add `basic-memory watch` CLI command
+
+- **#546**: Add cloud discovery touchpoints to CLI and MCP
+
+- **#572**: CLI analytics via Umami event collector
+
+- Replace project info with htop-inspired dashboard
+
+- Merge `search_by_metadata` into `search_notes` with optional query
+
 - Add `--strip-frontmatter` to `basic-memory tool read-note`
-  - Default behavior is unchanged: `content` still includes raw markdown with frontmatter.
-  - With `--strip-frontmatter`, both text and JSON modes return body-only markdown content.
-  - JSON output now includes an additive `frontmatter` field with parsed YAML metadata (or `null`
-    when no valid opening frontmatter block exists).
+
+- Add `destination_folder` parameter to `move_note` tool
+
+### Bug Fixes
+
+- **#644**: Fix default project resolution in cloud mode
+  - ChatGPT search/fetch tools broken in cloud mode
+  - `resolve_project_parameter` falls back to projects API
+
+- **#638**: Restore API backward compatibility for v0.18.x clients
+
+- **#637**: Create backup before config migration overwrites old format
+
+- **#636**: `list_workspaces` bypasses factory pattern on cloud MCP server
+
+- **#631**: `build_context` related_results schema validation failure
+
+- **#613**: Reduce excessive log volume by demoting per-request noise to DEBUG
+
+- **#612**: Handle quoted picoschema enum strings in YAML frontmatter
+
+- **#607**: Guard against closed streams in promo and missing vector tables
+
+- **#606**: Accept null for `expected_replacements` in `edit_note`
+
+- **#595**: `recent_activity` dedup and pagination across MCP tools
+
+- **#593**: Backend-specific distance-to-similarity conversion
+
+- **#582**: Use LinkResolver fallback in `build_context` for flexible identifier matching
+
+- **#577**: Replace RRF with score-based fusion in hybrid search
+
+- **#575**: Remove hardcoded "main" default from `default_project`
+
+- **#534**: Speed up `bm --version` startup
+
+- Fix semantic embeddings not generated on fresh DB or upgrade
+
+- Clarify `search_notes` parameter naming and fix `note_types` case sensitivity
+
+- Parse `tag:` prefix at MCP tool level to avoid hybrid search failure
+
+- Cap sqlite-vec knn k parameter at 4096 limit
+
+- Parameterize SQL queries in search repository type filters
+
+- Coerce list frontmatter values to strings for title and type fields
+
+- Avoid `Post(**metadata)` crash when frontmatter contains 'content' or 'handler' keys
+
+- Upgrade cryptography and python-multipart for security advisories
+
+### Internal
+
+- **#594**: Add `ty` as supplemental type checker
+- Batched vector sync orchestration across repositories
+- FastEmbed parallel guardrails and provider caching
+- Improved cloud CLI status and error messages
+- CI coverage and Postgres test fixes
 
 ## v0.18.5 (2026-02-13)
 

README.md

@@ -13,7 +13,7 @@
 - **Cloud is optional.** The local-first open-source workflow continues as always.
 - **OSS discount:** use code `BMFOSS` for 20% off for 3 months.
 
-[Sign up now →](https://basicmemory.com)
+[Sign up now →](https://basicmemory.com?utm_source=github&utm_medium=referral&utm_campaign=readme)
 
 with a 7 day free trial
 
@@ -23,8 +23,21 @@ Basic Memory lets you build persistent knowledge through natural conversations w
 Claude, while keeping everything in simple Markdown files on your computer. It uses the Model Context Protocol (MCP) to
 enable any compatible LLM to read and write to your local knowledge base.
 
-- Website: https://basicmemory.com
-- Documentation: https://docs.basicmemory.com
+## What's New in v0.19.0
+
+- **Semantic Vector Search** — find notes by meaning, not just keywords. Combines full-text and vector similarity for hybrid search with FastEmbed embeddings.
+- **Schema System** — infer, validate, and diff the structure of your knowledge base with `schema_infer`, `schema_validate`, and `schema_diff` tools.
+- **Per-Project Cloud Routing** — route individual projects through the cloud while others stay local, using API key authentication (`basic-memory project set-cloud`).
+- **FastMCP 3.0** — upgraded to FastMCP 3.0 with tool annotations for better client integration.
+- **CLI Overhaul** — JSON output mode (`--json`) for scripting, workspace-aware commands, and an htop-inspired project dashboard.
+- **Smarter Editing** — `edit_note` append/prepend auto-creates notes if they don't exist; `write_note` has an overwrite guard to prevent accidental data loss.
+- **Richer Search Results** — matched chunk text returned in search results for better context.
+
+See the full [CHANGELOG](CHANGELOG.md) for details.
+
+- Website: [basicmemory.com](https://basicmemory.com?utm_source=github&utm_medium=referral&utm_campaign=readme)
+- Documentation: [docs.basicmemory.com](https://docs.basicmemory.com?utm_source=github&utm_medium=referral&utm_campaign=readme)
+- Community: [Discord](https://discord.gg/tyvKNccgqN?utm_source=github&utm_medium=referral&utm_campaign=readme)
 
 ## Pick up your conversation right where you left off
 
@@ -62,6 +75,36 @@ uv tool install basic-memory
 
 You can view shared context via files in `~/basic-memory` (default directory location).
 
+## Automatic Updates
+
+Basic Memory includes a default-on auto-update flow for CLI installs.
+
+- **Auto-install supported:** `uv tool` and Homebrew installs
+- **Default check interval:** every 24 hours (`86400` seconds)
+- **MCP-safe behavior:** update checks run silently in `basic-memory mcp` mode
+- **`uvx` behavior:** skipped (runtime is ephemeral and managed by `uvx`)
+
+Manual update commands:
+
+```bash
+# Check now and install if supported
+bm update
+
+# Check only, do not install
+bm update --check
+```
+
+Config options in `~/.basic-memory/config.json`:
+
+```json
+{
+  "auto_update": true,
+  "update_check_interval": 86400
+}
+```
+
+To disable automatic updates, set `"auto_update": false`.
+
 ## Why Basic Memory?
 
 Most LLM interactions are ephemeral - you ask a question, get an answer, and everything is forgotten. Each conversation
@@ -438,8 +481,7 @@ list_directory(dir_name, depth) - Browse directory contents with filtering
 **Search & Discovery:**
 ```
 search(query, page, page_size) - Search across your knowledge base
-search_notes(query, page, page_size, search_type, types, entity_types, after_date, metadata_filters, tags, status, project) - Search with filters
-search_by_metadata(filters, limit, offset, project) - Structured frontmatter search
+search_notes(query, page, page_size, search_type, types, entity_types, after_date, metadata_filters, tags, status, project) - Search with filters (query is optional for filter-only searches)
 ```
 
 **Project Management:**
@@ -476,13 +518,13 @@ canvas(nodes, edges, title, folder) - Generate knowledge visualizations
 
 ## Futher info
 
-See the [Documentation](https://docs.basicmemory.com) for more info, including:
+See the [Documentation](https://docs.basicmemory.com?utm_source=github&utm_medium=referral&utm_campaign=readme) for more info, including:
 
-- [Complete User Guide](https://docs.basicmemory.com/user-guide/)
-- [CLI tools](https://docs.basicmemory.com/guides/cli-reference/)
-- [Cloud CLI and Sync](https://docs.basicmemory.com/guides/cloud-cli/)
-- [Managing multiple Projects](https://docs.basicmemory.com/guides/cli-reference/#project)
-- [Importing data from OpenAI/Claude Projects](https://docs.basicmemory.com/guides/cli-reference/#import)
+- [Complete User Guide](https://docs.basicmemory.com/user-guide/?utm_source=github&utm_medium=referral&utm_campaign=readme)
+- [CLI tools](https://docs.basicmemory.com/guides/cli-reference/?utm_source=github&utm_medium=referral&utm_campaign=readme)
+- [Cloud CLI and Sync](https://docs.basicmemory.com/guides/cloud-cli/?utm_source=github&utm_medium=referral&utm_campaign=readme)
+- [Managing multiple Projects](https://docs.basicmemory.com/guides/cli-reference/?utm_source=github&utm_medium=referral&utm_campaign=readme#project)
+- [Importing data from OpenAI/Claude Projects](https://docs.basicmemory.com/guides/cli-reference/?utm_source=github&utm_medium=referral&utm_campaign=readme#import)
 
 ## Telemetry
 
@@ -635,4 +677,4 @@ and submitting PRs.
  </picture>
 </a>
 
-Built with ♥️ by Basic Machines
+Built with ♥️ by [Basic Machines](https://basicmachines.co?utm_source=github&utm_medium=referral&utm_campaign=readme)

docs/ai-assistant-guide-extended.md

@@ -427,6 +427,8 @@ await write_note(
 )
 ```
 
+> **Important**: `write_note` errors if the note already exists. Use `edit_note` for incremental changes, or pass `overwrite=True` to replace.
+
 **Well-structured note**:
 
 ```python
@@ -760,6 +762,9 @@ notes = await read_note(
     identifier="memory://specs/*",
     project="main"
 )
+
+# Cross-project URL (auto-routes to the correct project)
+note = await read_note(identifier="memory://research/specs/api-design")
 ```
 
 ```python
@@ -1060,16 +1065,19 @@ results = await search_notes(
     project="main"
 )
 
-# Metadata-only search
-results = await search_by_metadata(
-    filters={"type": "spec", "status": "in-progress"},
+# Metadata-only search (no query needed)
+results = await search_notes(
+    metadata_filters={"type": "spec", "status": "in-progress"},
     project="main"
 )
 ```
 
 ### Search Types
 
-**Text search (default)**:
+Available types: `"text"`, `"title"`, `"permalink"`, `"vector"`/`"semantic"`, `"hybrid"`.
+Default is `"hybrid"` when semantic search is enabled, `"text"` otherwise.
+
+**Text search**:
 
 ```python
 # Full-text search across all content
@@ -1080,15 +1088,50 @@ results = await search_notes(
 )
 ```
 
-**Semantic search**:
+**Title and permalink search**:
+
+```python
+# Search by title only
+results = await search_notes(query="API Design", search_type="title", project="main")
+
+# Search by permalink
+results = await search_notes(query="specs/api-design", search_type="permalink", project="main")
+```
+
+**Semantic/vector search**:
 
 ```python
 # Semantic/vector search (if enabled)
 results = await search_notes(
     query="user login security",
-    search_type="semantic",
+    search_type="semantic",  # or "vector"
     project="main"
 )
+
+# Override similarity threshold
+results = await search_notes(
+    query="user login security",
+    search_type="semantic",
+    min_similarity=0.5,
+    project="main"
+)
+```
+
+**Hybrid search** (combines text + semantic):
+
+```python
+results = await search_notes(
+    query="authentication best practices",
+    search_type="hybrid",
+    project="main"
+)
+```
+
+**Tag shorthand in query**:
+
+```python
+# Use tag: prefix as shorthand
+results = await search_notes(query="tag:security", project="main")
 ```
 
 ### Search Response
@@ -2161,6 +2204,31 @@ active_project = projects[0]["name"]
 results = await search_notes(query="test", project=active_project)
 ```
 
+### Note Already Exists
+
+**Error**: `write_note` called for a note that already exists
+
+**Solution**:
+
+```python
+# Preferred: use edit_note for incremental updates
+await edit_note(
+    identifier="Existing Topic",
+    operation="append",
+    content="\n- [update] new information",
+    project="main"
+)
+
+# Alternative: replace the entire note
+await write_note(
+    title="Existing Topic",
+    content="# Existing Topic\n...",
+    folder="notes",
+    overwrite=True,
+    project="main"
+)
+```
+
 ### Entity Not Found
 
 **Error**: Note doesn't exist
@@ -2716,14 +2784,15 @@ await write_note(
 
 ### Content Management
 
-**write_note(title, content, folder, tags, note_type, project)**
-- Create or update markdown notes
+**write_note(title, content, folder, tags, note_type, overwrite, project)**
+- Create new markdown notes (errors if note already exists unless overwrite=True)
 - Parameters:
   - `title` (required): Note title
   - `content` (required): Markdown content
   - `folder` (required): Destination folder
   - `tags` (optional): List of tags
   - `note_type` (optional): Type of note (stored in frontmatter). Can be "note", "person", "meeting", "guide", etc.
+  - `overwrite` (optional): Set to True to replace an existing note (default: error if exists)
   - `project` (required unless default_project_mode): Target project
 - Returns: Created/updated entity with permalink
 - Example:
@@ -2890,19 +2959,20 @@ contents = await list_directory(
 
 ### Search & Discovery
 
-**search_notes(query, page, page_size, search_type, types, entity_types, after_date, metadata_filters, tags, status, project)**
+**search_notes(query, page, page_size, search_type, types, entity_types, after_date, metadata_filters, tags, status, min_similarity, project)**
 - Search across knowledge base
 - Parameters:
-  - `query` (required): Search query
+  - `query` (optional): Search query (not required for filter-only searches)
   - `page` (optional): Page number (default: 1)
   - `page_size` (optional): Results per page (default: 10)
-  - `search_type` (optional): "text" or "semantic"
+  - `search_type` (optional): "text", "title", "permalink", "vector"/"semantic", "hybrid" (default: "hybrid" when semantic enabled, "text" otherwise)
   - `types` (optional): Entity type filter
   - `entity_types` (optional): Observation category filter
   - `after_date` (optional): Date filter (ISO format)
-  - `metadata_filters` (optional): Structured frontmatter filters (dict)
-  - `tags` (optional): Frontmatter tags filter (list)
+  - `metadata_filters` (optional): Structured frontmatter filters (dict, supports `$in`, `$gt`, `$gte`, `$lt`, `$lte`, `$between` operators)
+  - `tags` (optional): Frontmatter tags filter (list); also available via `tag:` query shorthand
   - `status` (optional): Frontmatter status filter (string)
+  - `min_similarity` (optional): Override similarity threshold for vector/hybrid search
   - `project` (required unless default_project_mode): Target project
 - Returns: Matching entities with scores
 - Example:
@@ -2915,18 +2985,11 @@ results = await search_notes(
 )
 ```
 
-**search_by_metadata(filters, limit, offset, project)**
-- Metadata-only search using structured frontmatter
-- Parameters:
-  - `filters` (required): Dict of field -> value (supports $in, $gt/$gte/$lt/$lte, $between)
-  - `limit` (optional): Max results (default: 20)
-  - `offset` (optional): Pagination offset (default: 0)
-  - `project` (required unless default_project_mode): Target project
-- Returns: Matching entities
-- Example:
+**Metadata-only search (via search_notes)**
+- Use `search_notes` with `metadata_filters` and no `query` for metadata-only searches:
 ```python
-results = await search_by_metadata(
-    filters={"type": "spec", "status": "in-progress"},
+results = await search_notes(
+    metadata_filters={"type": "spec", "status": "in-progress"},
     project="main"
 )
 ```
@@ -2978,6 +3041,15 @@ await delete_project(project_name="old-project")
 status = await sync_status(project="main")
 ```
 
+**list_workspaces()**
+- List available workspaces (cloud)
+- Parameters: None
+- Returns: List of workspaces with metadata
+- Example:
+```python
+workspaces = await list_workspaces()
+```
+
 ### Visualization
 
 **canvas(nodes, edges, title, folder, project)**
@@ -3246,8 +3318,8 @@ await edit_note(
     project="main"
 )
 
-# Avoid: Complete rewrite
-# (unless necessary for major restructuring)
+# When full rewrite is needed, use overwrite=True
+await write_note(title="Note", content="...", folder="notes", overwrite=True)
 ```
 
 ### 14. Tagging Strategy

docs/logfire-instrumentation-strategy.md

@@ -0,0 +1,499 @@
+# Logfire Instrumentation Strategy
+
+## Why
+
+We want Logfire in Basic Memory for two specific use cases:
+
+1. Local development and performance investigation
+2. Cloud deployments where Basic Memory runs inside Basic Memory Cloud
+
+This instrumentation must be:
+
+- Disabled by default
+- Useful when enabled
+- Safe for local-first users
+- Searchable in Logfire over time
+
+The previous integration added telemetry, but it leaned too much on generic framework instrumentation. That created noisy spans with weak names and made the trace view harder to navigate. This strategy favors manual instrumentation around Basic Memory's real units of work.
+
+## Core Principles
+
+### 1. Default-off
+
+Basic Memory should ship with Logfire disabled unless the operator explicitly enables it.
+
+That means:
+
+- no required token for normal local usage
+- no surprise outbound telemetry
+- no behavior change for existing users
+
+### 2. Manual spans over automatic framework spans
+
+We should not rely on broad auto-instrumentation for FastAPI, MCP, SQLAlchemy, or HTTP as the primary experience.
+
+Why:
+
+- auto-generated span names are often generic
+- routes and middleware produce too many low-signal spans
+- it becomes harder to answer product questions like "why was `write_note` slow?" or "where did sync time go?"
+
+The preferred model is:
+
+- one meaningful root span per high-level operation
+- a small number of child spans for important phases
+- optional targeted instrumentation only where it adds clear value
+
+### 3. Logs must live inside traces
+
+Basic Memory already uses `loguru` pervasively. The Logfire integration should preserve that and make those logs visible inside the active trace/span context.
+
+If traces exist but the logs are detached from them, the integration is not doing its job.
+
+### 4. Stable names, selective attributes
+
+Span names should describe the operation class, not the specific input.
+
+Good:
+
+- `mcp.tool.write_note`
+- `sync.project.scan`
+- `search.execute`
+- `routing.resolve_project`
+
+Bad:
+
+- `Searching for "foo bar baz"`
+- `POST /v2/projects/123/search/`
+- `write note to /specs/api.md`
+
+Dynamic values belong in attributes, not in the span name.
+
+## What We Should Not Do
+
+### Avoid broad FastAPI auto-instrumentation
+
+We should not turn on `instrument_fastapi()` and treat that as the main telemetry story.
+
+It may still be useful in narrowly scoped debugging, but it should not define the production trace shape. The meaningful root spans should come from Basic Memory's own entrypoints and service boundaries.
+
+### Avoid per-file spans by default
+
+`sync` can process many files. A span per file will explode trace cardinality and make performance views noisy.
+
+Default behavior should be:
+
+- one span for the project sync
+- child spans for scan, move handling, delete handling, markdown sync batch, relation resolution, embedding sync, watermark update
+- per-file spans only for failures or very slow outliers
+
+### Avoid high-cardinality attributes on every span
+
+Do not attach large or highly variable values everywhere:
+
+- raw note content
+- file bodies
+- long search text
+- arbitrary metadata blobs
+- unique IDs that make every span shape distinct
+
+Prefer compact, queryable attributes:
+
+- `project_name`
+- `workspace_id`
+- `route_mode`
+- `scan_type`
+- `file_count`
+- `result_count`
+- `search_type`
+- `retrieval_mode`
+- `duration_ms`
+
+## Proposed Architecture
+
+Add a dedicated telemetry module in core Basic Memory, separate from logging setup.
+
+Suggested shape:
+
+```python
+# basic_memory/telemetry.py
+
+def configure_telemetry(service_name: str, *, enable_logfire: bool) -> None: ...
+def telemetry_enabled() -> bool: ...
+def span(name: str, **attrs): ...
+def bind_telemetry_context(**attrs): ...
+```
+
+This module should:
+
+- configure Logfire only when explicitly enabled
+- set up the Logfire `loguru` handler
+- expose lightweight helpers so application code does not import `logfire` directly everywhere
+- degrade cleanly to no-op behavior when disabled
+
+This keeps the rest of the codebase readable and makes it easy to reason about what telemetry is doing.
+
+## Logging Integration Strategy
+
+### Goal
+
+When a span is active, logs emitted through `loguru` during that operation should show up in the same trace.
+
+### Preferred design
+
+1. Configure Logfire once in the telemetry bootstrap
+2. Add the Logfire `loguru` handler to the existing `loguru` configuration
+3. At operation boundaries, bind stable contextual fields with `loguru`
+4. Let logs emitted inside the span inherit the active trace context
+
+### Context to bind
+
+Bind only the fields that help correlate work across the system:
+
+- `service_name`
+- `entrypoint`
+- `project_name`
+- `workspace_id`
+- `route_mode`
+- `tool_name`
+- `command_name`
+
+This binding should happen at the root of an operation, not deep in leaf functions.
+
+### Important nuance
+
+We should not try to encode the entire trace model into logger extras. The logger context should be a human-meaningful slice of the active operation. Trace linkage comes from the active Logfire/OpenTelemetry context; logger extras are there to improve searchability and readability.
+
+## Span Model
+
+### Root spans
+
+Each user-visible or system-visible operation should get one root span.
+
+Examples:
+
+- `cli.command.status`
+- `cli.command.project_sync`
+- `api.request.search`
+- `mcp.tool.write_note`
+- `mcp.tool.read_note`
+- `mcp.tool.search_notes`
+- `sync.project.run`
+- `db.semantic_backfill`
+
+### Child spans
+
+Child spans should represent real phases whose duration we care about.
+
+Examples:
+
+- `routing.client_session`
+- `routing.resolve_project`
+- `routing.resolve_workspace`
+- `api.search.execute`
+- `sync.project.scan`
+- `sync.project.detect_moves`
+- `sync.project.apply_changes`
+- `sync.project.resolve_relations`
+- `sync.project.sync_embeddings`
+- `sync.file.markdown`
+- `sync.file.regular`
+- `search.execute`
+- `search.relaxed_fts_retry`
+- `db.init`
+- `db.migrate`
+
+### Span naming rules
+
+- Use dot-separated names
+- Start with subsystem
+- Keep the verb at the end
+- Keep names stable across runs
+- Never include request-specific text in the span name
+
+## Attribute Taxonomy
+
+### Required attributes on root spans
+
+Every root span should have a small common set:
+
+- `service_name`
+- `entrypoint`
+- `project_name` when applicable
+- `workspace_id` when applicable
+- `route_mode` with values like `local_asgi`, `cloud_proxy`, `factory`
+
+### Operation-specific attributes
+
+Examples:
+
+For search:
+
+- `search_type`
+- `retrieval_mode`
+- `page`
+- `page_size`
+- `result_count`
+- `fallback_used`
+
+For sync:
+
+- `scan_type`
+- `force_full`
+- `new_count`
+- `modified_count`
+- `deleted_count`
+- `move_count`
+- `skipped_count`
+- `embeddings_enabled`
+
+For note operations:
+
+- `tool_name`
+- `note_type`
+- `directory`
+- `overwrite`
+- `output_format`
+
+### Attributes to avoid by default
+
+- full `query.text`
+- full note titles if they create privacy or cardinality issues
+- file content
+- raw frontmatter
+- raw HTTP bodies
+
+If we need richer payloads for a local debugging session, that should be an explicit temporary mode, not the default telemetry shape.
+
+## Instrumentation Plan By Layer
+
+### 1. Entrypoints
+
+Instrument these first:
+
+- `cli.app` callback and major commands
+- API lifespan and selected routers
+- MCP server lifespan
+- MCP tool entrypoints
+
+Why:
+
+- this establishes clean root spans
+- it gives us trace boundaries that match how users think about the product
+
+### 2. Routing and context resolution
+
+Instrument:
+
+- client routing decisions
+- workspace resolution
+- project resolution
+- default-project fallback
+
+Why:
+
+- Basic Memory has local/cloud/per-project routing logic
+- when something is slow or surprising, we need to know which path was taken
+
+### 3. Sync and indexing
+
+This is the highest-value area to instrument deeply.
+
+Instrument:
+
+- sync root
+- scan strategy decision
+- filesystem scan
+- move detection
+- delete handling
+- markdown sync phase
+- relation resolution
+- vector embedding sync
+- scan watermark update
+
+Why:
+
+- this is where performance work will happen
+- cloud and local both benefit from this visibility
+
+### 4. Search
+
+Instrument:
+
+- search execution
+- retrieval mode
+- relaxed FTS fallback
+- result shaping
+
+Why:
+
+- search is user-facing and latency-sensitive
+- hybrid/vector/FTS paths need to be distinguishable
+
+### 5. Database and initialization
+
+Instrument selectively:
+
+- DB init
+- migrations
+- semantic backfill
+- connection mode selection
+
+Avoid full automatic SQL span firehose by default.
+
+## Recommended Rollout Phases
+
+## Task List
+
+- [x] Phase 1: Bootstrap and config gating
+- [x] Phase 2: Root spans for entrypoints and primary operations
+- [x] Phase 3: Child spans for sync, search, and routing
+- [x] Phase 4: Failure-focused detail and final verification
+- [x] Phase 5: Loguru context binding and scoped context inheritance
+
+## Recommended Rollout Phases
+
+### Phase 1: Bootstrap and config gating
+
+Add:
+
+- telemetry bootstrap module
+- config/env gating
+- `loguru` + Logfire handler integration
+
+This gives immediate value with low noise.
+
+### Phase 2: Root spans for entrypoints and primary operations
+
+Add:
+
+- root spans for CLI, API, MCP, and main MCP tools
+- stable root attributes for project, workspace, route mode, and operation type
+
+This gives us clean top-level traces that match how users think about the product.
+
+### Phase 3: Child spans for sync, search, and routing
+
+Add child spans to:
+
+- sync
+- search
+- routing
+
+This is the main performance-investigation layer.
+
+### Phase 4: Failure-focused detail
+
+Add selective deeper spans/log enrichment for:
+
+- sync failures
+- relation resolution failures
+- slow file operations
+- cloud routing/auth failures
+
+This keeps normal traces clean while improving debuggability.
+
+### Phase 5: Loguru context binding and scoped context inheritance
+
+Add:
+
+- context-local telemetry state in `basic_memory.telemetry`
+- a shared `scope(...)` helper that opens a span and binds stable logger context together
+- context inheritance for routing, sync, and search so downstream `loguru` logs carry the active operation fields
+
+This makes the trace view and the log stream tell the same story without forcing logger rewrites across the codebase.
+
+## Local Dev Playbook
+
+The fastest way to sanity-check the current trace shape is:
+
+```bash
+LOGFIRE_TOKEN=lf_... just telemetry-smoke
+```
+
+What this does:
+
+- creates an isolated temp home, config dir, and project path
+- enables Logfire for the run
+- automatically exports to Logfire when `LOGFIRE_TOKEN` is present
+- defaults `BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=false` so the smoke run stays fast and trace-friendly
+- disables promo telemetry so the trace is about Basic Memory work, not analytics noise
+- runs a small CLI workflow:
+  - `project add`
+  - `tool write-note`
+  - `tool read-note`
+  - `tool edit-note`
+  - `tool build-context`
+  - `tool search-notes`
+  - `doctor`
+
+If you want to exercise the instrumentation without exporting anything upstream:
+
+```bash
+BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE=false just telemetry-smoke
+```
+
+If you want the smoke run to include vector or hybrid retrieval spans too:
+
+```bash
+LOGFIRE_TOKEN=lf_... BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED=true just telemetry-smoke
+```
+
+The recipe sets `BASIC_MEMORY_LOGFIRE_ENVIRONMENT=telemetry-smoke` by default so these traces are easy to isolate in Logfire. Override it if you want the smoke traces grouped under a different environment name.
+
+### What to look for
+
+You should see a small set of comparable root spans rather than a framework-generated span forest:
+
+- `cli.command.project`
+- `cli.command.tool`
+- `mcp.tool.write_note`
+- `mcp.tool.read_note`
+- `mcp.tool.edit_note`
+- `mcp.tool.build_context`
+- `mcp.tool.search_notes`
+- `sync.project.run`
+
+You should also see correlated logs under those traces with stable fields like:
+
+- `project_name`
+- `route_mode`
+- `tool_name`
+- `entrypoint`
+
+### Expected nuance
+
+`doctor` creates its own temporary project on purpose. That means the sync trace will usually show a different project name than the `telemetry-smoke` write/search traces. That is fine for smoke testing because the goal is to confirm:
+
+- root span names are meaningful
+- scoped logs stay attached to the active trace
+- routing, tool, search, and sync phases are easy to distinguish
+
+## Validation Checklist
+
+We should consider the integration successful when the following are true:
+
+1. With telemetry disabled, Basic Memory behaves exactly as it does today.
+2. With telemetry enabled, one user action produces one obvious root span.
+3. Logs emitted during that action are visible inside the same trace.
+4. A search in Logfire for `mcp.tool.write_note` or `sync.project.run` returns comparable spans across runs.
+5. Trace views show phase timing clearly without drowning in framework noise.
+6. Sensitive payloads are not captured by default.
+
+## Immediate Implementation Direction
+
+When we start coding, the first pass should be:
+
+1. Add `basic_memory.telemetry`
+2. Add config/env switches for `enabled`, `send_to_logfire`, and service name
+3. Wire telemetry bootstrap into CLI, API, and MCP entrypoints
+4. Configure `loguru` to emit to both existing sinks and the Logfire handler when enabled
+5. Add manual root spans around:
+   - CLI commands
+   - API request handlers we care about
+   - MCP tool entrypoints
+   - sync root
+   - search root
+6. Add child spans to the sync and routing phases only after the root span model feels clean
+
+That gives us a strong foundation without repeating the earlier "turn on instrumentation everywhere" approach.

docs/metadata-search.md

@@ -2,14 +2,9 @@
 
 Basic Memory automatically indexes custom frontmatter fields so you can query them with structured filters. Any YAML key in a note's frontmatter beyond the standard set (`title`, `type`, `tags`, `permalink`, `schema`) is stored as `entity_metadata` and becomes searchable.
 
-## Two Ways to Query
+## Querying with `search_notes`
 
-| Tool | Use When |
-|------|----------|
-| `search_by_metadata` | You only need metadata filters (no text query) |
-| `search_notes` | You want to combine a text query with metadata filters |
-
-Both tools accept the same filter syntax.
+`search_notes` is the single search tool for all queries — text, metadata filters, or both. The `query` parameter is optional, so you can use metadata filters alone without passing an empty string.
 
 ## Filter Syntax
 
@@ -88,45 +83,16 @@ This queries the `version` key inside a `schema` object in frontmatter.
 - `$in` and array-contains require non-empty lists.
 - `$between` requires exactly two values `[min, max]`.
 
-## MCP Tools
+## MCP Tool — `search_notes`
 
-### `search_by_metadata` — metadata-only search
-
-Searches entities by structured frontmatter metadata without a text query. Results are scoped to entity-level items.
-
-**Parameters:**
-
-| Parameter | Type | Required | Description |
-|-----------|------|----------|-------------|
-| `filters` | dict | Yes | Metadata filter dictionary (see syntax above) |
-| `project` | string | No | Project to search in (uses default if omitted) |
-| `limit` | int | No | Max results (default 20) |
-| `offset` | int | No | Skip N results for pagination (default 0) |
-
-**Example:**
-
-```python
-# Find all notes with status "in-progress"
-await search_by_metadata({"status": "in-progress"})
-
-# Find high-priority specs in the research project
-await search_by_metadata(
-    {"type": "spec", "priority": {"$in": ["high", "critical"]}},
-    project="research",
-    limit=10,
-)
-```
-
-### `search_notes` with metadata — combined text + metadata
-
-The `search_notes` tool accepts `metadata_filters`, `tags`, and `status` parameters alongside the text `query`. This lets you combine full-text search with structured filtering.
+`search_notes` is the single search tool for text queries, metadata filters, or both. The `query` parameter is optional.
 
 **Relevant parameters:**
 
 | Parameter | Type | Description |
 |-----------|------|-------------|
-| `query` | string | Text search query (can be empty when using only filters) |
-| `metadata_filters` | dict | Structured filter dict (same syntax as `search_by_metadata`) |
+| `query` | string (optional) | Text search query. Omit for filter-only searches. |
+| `metadata_filters` | dict | Structured filter dict (see syntax above) |
 | `tags` | list[str] | Convenience shorthand — merged into `metadata_filters["tags"]` |
 | `status` | string | Convenience shorthand — merged into `metadata_filters["status"]` |
 
@@ -138,8 +104,8 @@ The `search_notes` tool accepts `metadata_filters`, `tags`, and `status` paramet
 # Text search filtered by metadata
 await search_notes("authentication", metadata_filters={"status": "draft"})
 
-# Filter-only search (empty query)
-await search_notes("", metadata_filters={"type": "spec"})
+# Filter-only search (no query needed)
+await search_notes(metadata_filters={"type": "spec"})
 
 # Combine text, tags shortcut, and metadata
 await search_notes(
@@ -150,7 +116,7 @@ await search_notes(
 
 # Convenience shortcuts
 await search_notes("planning", status="active")
-await search_notes("", tags=["tier1", "alpha"])
+await search_notes(tags=["tier1", "alpha"])
 ```
 
 ## Tag Search Shortcuts
@@ -260,19 +226,19 @@ confidence: 0.6
 
 ```python
 # Find all in-progress specs
-await search_by_metadata({"status": "in-progress", "type": "spec"})
+await search_notes(metadata_filters={"status": "in-progress", "type": "spec"})
 # → Auth Design
 
 # Find high-confidence specs
-await search_by_metadata({"confidence": {"$gt": 0.7}})
+await search_notes(metadata_filters={"confidence": {"$gt": 0.7}})
 # → Auth Design (confidence: 0.85)
 
 # Find specs with priority high or medium
-await search_by_metadata({"priority": {"$in": ["high", "medium"]}})
+await search_notes(metadata_filters={"priority": {"$in": ["high", "medium"]}})
 # → Auth Design, Search Redesign
 
 # Find specs in a confidence range
-await search_by_metadata({"confidence": {"$between": [0.5, 0.9]}})
+await search_notes(metadata_filters={"confidence": {"$between": [0.5, 0.9]}})
 # → Auth Design (0.85), Search Redesign (0.6)
 
 # Find notes tagged with security

docs/releases/v0.19.0.md

@@ -4,7 +4,7 @@
 
 v0.19.0 is a major release that introduces semantic vector search, a schema validation system,
 project-prefixed permalinks, per-project cloud routing, and a significant upgrade to FastMCP 3.0.
-It includes 66 commits since v0.18.0 spanning new features, architectural improvements, and
+It includes 90+ commits since v0.18.0 spanning new features, architectural improvements, and
 stability fixes across both SQLite and Postgres backends.
 
 ---
@@ -16,6 +16,7 @@ stability fixes across both SQLite and Postgres backends.
 Full vector and hybrid search for SQLite (via sqlite-vec) and Postgres (via pgvector).
 
 - **Hybrid search mode** combines full-text search (FTS) with vector similarity for best results
+- **Score-based fusion** replaces RRF for hybrid ranking — `max(vec, fts) + 0.3 * min(vec, fts)` preserves dominant signals and rewards dual-source agreement (#577)
 - **Default search mode** is now `hybrid` when semantic search is enabled, `text` when disabled
 - Embedding providers: FastEmbed (local, default) or OpenAI API
 - Configurable similarity threshold via `semantic_min_similarity` (default 0.55)
@@ -23,6 +24,7 @@ Full vector and hybrid search for SQLite (via sqlite-vec) and Postgres (via pgve
 - Auto-backfill: existing entities get embeddings generated on first startup
 - Backend-specific distance-to-similarity conversion (cosine for SQLite, inner product for Postgres)
 - FTS fallback: if semantic dependencies are missing, search gracefully degrades to text-only
+- sqlite-vec knn `k` parameter capped at 4096 to prevent backend errors
 
 **Configuration:**
 ```json
@@ -84,6 +86,29 @@ Cloud projects can target specific workspaces for multi-tenant environments.
 
 ## New Tools and Capabilities
 
+### Dashboard (`bm project info`)
+
+`bm project info` now displays an htop-inspired compact dashboard with:
+
+- Horizontal bar charts for note types (top 5)
+- Embedding coverage bar with Unicode block characters
+- Colored status dots for at-a-glance health
+- `EmbeddingStatus` schema and `get_embedding_status()` service method for programmatic access
+
+### Unified Metadata Search
+
+`search_by_metadata` has been merged into `search_notes` — one tool for all searches.
+`query` is now optional, so you can search purely by frontmatter metadata.
+
+```
+search_notes(metadata_filters={"status": "in-progress"})
+search_notes(metadata_filters={"tags": ["security", "oauth"]})
+search_notes(metadata_filters={"priority": {"$in": ["high", "critical"]}})
+search_notes(metadata_filters={"schema.confidence": {"$gt": 0.7}})
+search_notes(tags=["security"])  # convenience shorthand
+search_notes(status="draft")     # convenience shorthand
+```
+
 ### JSON Output Mode
 
 All MCP tools now support `output_format="json"` for machine-readable responses.
@@ -92,17 +117,6 @@ All MCP tools now support `output_format="json"` for machine-readable responses.
 - `build_context` defaults to `"json"` with slimmed payloads (redundant fields stripped)
 - CLI tool commands support `--format json` flag
 
-### Structured Metadata Search
-
-New `search_by_metadata` tool for searching by frontmatter fields.
-
-```
-search_by_metadata({"status": "in-progress"})
-search_by_metadata({"tags": ["security", "oauth"]})
-search_by_metadata({"priority": {"$in": ["high", "critical"]}})
-search_by_metadata({"schema.confidence": {"$gt": 0.7}})
-```
-
 ### `tag:` Search Shorthand
 
 Search by tag using convenient shorthand syntax.
@@ -116,14 +130,32 @@ search_notes("tag:coffee AND tag:brewing")
 
 Entities now track `created_by` and `last_updated_by` fields for attribution.
 
-### Matched Chunk Text in Search
+### Improved Search Result Content (#609)
 
-Search results now include `matched_chunk` field showing the specific text that matched.
+Search results now surface more relevant context:
+
+- `matched_chunk_text` populated for FTS-only hybrid results (no more fallback to truncated content)
+- `TOP_CHUNKS_PER_RESULT` increased from 3 to 5, catching answers deeper in large notes (~2700 → ~4500 chars)
+- `CONTENT_DISPLAY_LIMIT` doubled from 2000 to 4000 chars for results without matched chunks
+
+### `write_note` Overwrite Guard (#632)
+
+`write_note` is now non-idempotent by default. If a note already exists, the tool returns an
+error instead of silently overwriting. Pass `overwrite=True` to replace, or use `edit_note`
+for incremental updates. Config option `write_note_overwrite_default` restores the old upsert
+behavior.
 
 ---
 
 ## Architecture Changes
 
+### Score-Based Hybrid Fusion (#577)
+
+RRF (Reciprocal Rank Fusion) compressed all fused scores to ~0.016, destroying ranking
+differentiation. The new formula `max(vec, fts) + FUSION_BONUS * min(vec, fts)` preserves
+dominant signals and rewards dual-source agreement. Zero-score results now produce zero
+fused score instead of receiving a 0.1 weight floor.
+
 ### FastMCP 3.0 Upgrade
 
 Upgraded from FastMCP 2.12.3 to 3.0.1.
@@ -176,6 +208,19 @@ Docker-internal paths that don't exist locally.
 All `bm tool` subcommands support `--format json` for machine-readable output, enabling
 integration with scripts and plugins.
 
+### `--json` for Top-Level CLI Commands
+
+Five additional CLI commands now support `--json` for machine-readable output:
+
+- `bm status --json` — sync report with new/modified/deleted/moved files and skipped files
+- `bm project list --json` — structured project list with name, paths, routing mode, and defaults
+- `bm schema validate --json` — validation report with per-note pass/fail, warnings, and errors
+- `bm schema infer --json` — field frequency analysis and suggested schema definition
+- `bm schema diff --json` — drift report with new fields, dropped fields, and cardinality changes
+
+This complements the existing `bm project info --json` and `bm tool --format json` support,
+making all major CLI commands scriptable for CI pipelines and automation.
+
 ### Cloud Promo and Analytics
 
 - Cloud promo panel shown on first run or version bump with OSS discount code
@@ -188,6 +233,7 @@ integration with scripts and plugins.
 
 ## Bug Fixes
 
+- **#577**: RRF fusion compressed all hybrid scores to ~0.016, destroying ranking differentiation
 - **#582**: build_context returns empty results on valid note identifiers
 - **#575**: Remove hardcoded "main" default from default_project
 - **#595**: recent_activity dedup and pagination across MCP tools
@@ -200,6 +246,19 @@ integration with scripts and plugins.
 - **#533**: Fix recent_activity prompt defaults
 - **#530**: Prevent spurious `metadata: {}` in frontmatter output
 - **#601**: Return matched chunk text in search results
+- **#606**: Accept `null` for `expected_replacements` in `edit_note`
+- **#579, #607**: Guard against closed streams in promo panel and missing vector tables on shutdown
+- **#609**: FTS-only hybrid results missing `matched_chunk_text`; content limits too conservative
+- **#631**: `build_context` related_results schema validation failure — replaced fragile `_slim_context()` stripping with Pydantic `exclude=True` field config
+- **#630**: Skip workspace resolution when client factory is active — prevents 401 errors in cloud MCP server mode
+- **#30**: `tag:` prefix query fails with hybrid search — moved tag prefix parsing to MCP tool level so it works with all search modes
+- **#31**: `search_notes` returns cluttered observation/relation-level results — now defaults to entity-level results
+- **#28**: `schema_infer` and `schema_diff` return raw Pydantic models as "undefined" in LLM output — added markdown formatters
+- Fix `schema_validate` identifier resolution (now uses LinkResolver) and text rendering (markdown formatter)
+- **#634**: `schema_validate` and `schema_diff` use stale database metadata instead of reading schema definitions from file — now reads frontmatter directly from the file with fallback to database metadata
+- Fix `Post(**metadata)` crash when frontmatter contains `content` or `handler` keys
+- Fix list-valued frontmatter fields (`title`, `type`) crashing on `.strip()` — now coerced to strings
+- Cap sqlite-vec knn `k` parameter at 4096 to prevent backend errors
 - Parameterize SQL queries in search repository type filters
 - Double-default display in project list
 - `ensure_frontmatter_on_sync` default changed to `True`
@@ -208,6 +267,13 @@ integration with scripts and plugins.
 
 ---
 
+## Security
+
+- Upgrade `cryptography` for CVE advisory
+- Upgrade `python-multipart` for security advisory
+
+---
+
 ## Internal / Developer
 
 - **#598**: Upgrade FastMCP 2.12.3 → 3.0.1 with tool annotations
@@ -217,6 +283,8 @@ integration with scripts and plugins.
 - **#596**: Fix CLI runtime defects and audit regressions
 - CLI refactoring and workspace-aware cloud project listing
 - Split and speed up PR test matrix in CI
+- Fix CI: collect coverage from test jobs instead of re-running all tests
+- Create `search_vector_chunks` in test fixtures for Postgres compatibility
 
 ---
 
@@ -235,9 +303,16 @@ integration with scripts and plugins.
 - **Semantic search dependencies** are now included by default. If sqlite-vec fails to load,
   search gracefully falls back to FTS. Run `bm reindex --embeddings` to generate embeddings
   for existing content.
+- **Hybrid search scoring** has changed from RRF to score-based fusion. Search result ordering
+  may differ — results should be more accurate with better score differentiation.
+- **`search_by_metadata`** is removed as a standalone tool. Use `search_notes` with
+  `metadata_filters` instead (same parameters, same behavior).
 - **Project-prefixed permalinks** are enabled by default. Existing notes keep their current
   permalinks until modified. Set `permalinks_include_project: false` to disable.
 - **Frontmatter on sync** is now enabled by default. Files without frontmatter will have it
   added on next sync. Set `ensure_frontmatter_on_sync: false` to preserve old behavior.
 - **Config migration** runs automatically for cloud projects with bisync — `local_sync_path`
   is promoted to `path` so filesystem operations work correctly.
+- **`write_note` is no longer idempotent** — calls to `write_note` for existing notes now
+  return an error unless `overwrite=True` is passed. Use `edit_note` for incremental changes,
+  or set `write_note_overwrite_default: true` in config to restore the old behavior.

docs/semantic-search.md

@@ -165,13 +165,13 @@ Returns results ranked by cosine similarity. Individual observations and relatio
 
 ### `hybrid`
 
-Combines FTS and vector results using reciprocal rank fusion (RRF). This is generally the best mode when you want both keyword precision and semantic recall.
+Combines FTS and vector results using score-based fusion. This is generally the best mode when you want both keyword precision and semantic recall.
 
 ```python
 search_notes("authentication security", search_type="hybrid")
 ```
 
-RRF merges the two ranked lists so that items appearing in both get a score boost, while items found by only one method still appear.
+Score-based fusion uses the formula `max(vec, fts) + bonus * min(vec, fts)` to preserve the dominant signal while rewarding results found by both methods.
 
 ### When to Use Which
 
@@ -236,14 +236,14 @@ Each chunk has a `source_hash` (SHA-256 of the chunk text). On re-sync, unchange
 
 ### Hybrid Fusion
 
-Hybrid search uses reciprocal rank fusion (RRF) to merge FTS and vector results:
+Hybrid search uses score-based fusion to merge FTS and vector results:
 
-1. Run FTS search to get keyword-ranked results
-2. Run vector search to get similarity-ranked results
-3. For each result, compute: `score = 1/(k + fts_rank) + 1/(k + vector_rank)` where `k = 60`
+1. Run FTS search to get keyword-ranked results; normalize scores to [0, 1]
+2. Run vector search to get similarity-ranked results (already [0, 1])
+3. For each result, compute: `fused = max(vec_score, fts_score) + 0.3 * min(vec_score, fts_score)`
 4. Sort by fused score
 
-Items found by both methods get a natural score boost. Items found by only one method still appear but rank lower.
+The dominant signal (whichever source scored higher) is preserved, and dual-source agreement adds a bonus. Unlike rank-based fusion, this approach retains score magnitude — a strong vector match stays strong even without an FTS hit.
 
 ### Observation-Level Results
 

justfile

@@ -205,6 +205,51 @@ doctor:
     BASIC_MEMORY_CONFIG_DIR="$TMP_CONFIG" \
     ./.venv/bin/python -m basic_memory.cli.main doctor --local
 
+# Run an isolated Logfire smoke workflow for local trace inspection
+telemetry-smoke:
+    #!/usr/bin/env bash
+    set -euo pipefail
+    TMP_HOME=$(mktemp -d)
+    TMP_CONFIG=$(mktemp -d)
+    TMP_PROJECT=$(mktemp -d)
+    export HOME="$TMP_HOME"
+    export BASIC_MEMORY_ENV="${BASIC_MEMORY_ENV:-dev}"
+    export BASIC_MEMORY_HOME="$TMP_PROJECT/home-root"
+    export BASIC_MEMORY_CONFIG_DIR="$TMP_CONFIG"
+    export BASIC_MEMORY_NO_PROMOS=1
+    export BASIC_MEMORY_LOG_LEVEL="${BASIC_MEMORY_LOG_LEVEL:-INFO}"
+    export BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED="${BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED:-false}"
+    export BASIC_MEMORY_LOGFIRE_ENABLED="${BASIC_MEMORY_LOGFIRE_ENABLED:-true}"
+    export BASIC_MEMORY_LOGFIRE_ENVIRONMENT="${BASIC_MEMORY_LOGFIRE_ENVIRONMENT:-telemetry-smoke}"
+    if [[ -z "${BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE:-}" ]]; then
+        if [[ -n "${LOGFIRE_TOKEN:-}" ]]; then
+            export BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE=true
+        else
+            export BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE=false
+        fi
+    fi
+    mkdir -p "$BASIC_MEMORY_HOME"
+    echo "Telemetry smoke setup:"
+    echo "  logfire_enabled=$BASIC_MEMORY_LOGFIRE_ENABLED"
+    echo "  send_to_logfire=$BASIC_MEMORY_LOGFIRE_SEND_TO_LOGFIRE"
+    echo "  log_level=$BASIC_MEMORY_LOG_LEVEL"
+    echo "  semantic_search_enabled=$BASIC_MEMORY_SEMANTIC_SEARCH_ENABLED"
+    echo "  logfire_environment=$BASIC_MEMORY_LOGFIRE_ENVIRONMENT"
+    echo "  project_path=$TMP_PROJECT"
+    ./.venv/bin/python -m basic_memory.cli.main project add telemetry-smoke "$TMP_PROJECT" --default --local
+    ./.venv/bin/python -m basic_memory.cli.main tool write-note --title "Telemetry Smoke" --folder notes --content "hello from smoke" --project telemetry-smoke --local
+    ./.venv/bin/python -m basic_memory.cli.main tool read-note notes/telemetry-smoke --project telemetry-smoke --local
+    ./.venv/bin/python -m basic_memory.cli.main tool edit-note notes/telemetry-smoke --operation append --content $'\n\nsmoke edit line' --project telemetry-smoke --local
+    ./.venv/bin/python -m basic_memory.cli.main tool build-context notes/telemetry-smoke --project telemetry-smoke --local --page-size 5 --max-related 5
+    ./.venv/bin/python -m basic_memory.cli.main tool search-notes telemetry --project telemetry-smoke --local
+    ./.venv/bin/python -m basic_memory.cli.main doctor --local
+    echo ""
+    echo "Telemetry smoke complete."
+    echo "Search Logfire for:"
+    echo "  service_name: basic-memory-cli"
+    echo "  environment: $BASIC_MEMORY_LOGFIRE_ENVIRONMENT"
+    echo "  span names: mcp.tool.write_note, mcp.tool.read_note, mcp.tool.edit_note, mcp.tool.build_context, mcp.tool.search_notes, sync.project.run"
+
 
 # Update all dependencies to latest versions
 update-deps:

llms-install.md

@@ -54,6 +54,22 @@ Or for a one-time sync:
 basic-memory sync
 ```
 
+### 4. Updating Basic Memory
+
+Basic Memory supports automatic updates by default for `uv tool` and Homebrew installs.
+
+For manual checks and upgrades:
+
+```bash
+# Check now and install if supported
+bm update
+
+# Check only, do not install
+bm update --check
+```
+
+To disable automatic updates, set `"auto_update": false` in `~/.basic-memory/config.json`.
+
 ## Configuration Options
 
 ### Custom Directory
@@ -125,4 +141,4 @@ If you encounter issues:
    cat ~/.basic-memory/basic-memory.log
    ```
 
-For more detailed information, refer to the [full documentation](https://memory.basicmachines.co/).
+For more detailed information, refer to the [full documentation](https://docs.basicmemory.com/).

pyproject.toml

@@ -58,6 +58,9 @@ Documentation = "https://github.com/basicmachines-co/basic-memory#readme"
 basic-memory = "basic_memory.cli.main:app"
 bm = "basic_memory.cli.main:app"
 
+[project.optional-dependencies]
+telemetry = ["logfire>=4.19.0"]
+
 [build-system]
 requires = ["hatchling", "uv-dynamic-versioning>=0.7.0"]
 build-backend = "hatchling.build"
@@ -83,6 +86,7 @@ target-version = "py312"
 
 [dependency-groups]
 dev = [
+    "logfire>=4.19.0",
     "gevent>=24.11.1",
     "icecream>=2.1.3",
     "pytest>=8.3.4",

server.json

@@ -6,12 +6,12 @@
     "url": "https://github.com/basicmachines-co/basic-memory.git",
     "source": "github"
   },
-  "version": "0.18.5",
+  "version": "0.20.3",
   "packages": [
     {
       "registryType": "pypi",
       "identifier": "basic-memory",
-      "version": "0.18.5",
+      "version": "0.20.3",
       "runtimeHint": "uvx",
       "runtimeArguments": [
         {"type": "positional", "value": "basic-memory"},

src/basic_memory/__init__.py

@@ -1,7 +1,7 @@
 """basic-memory - Local-first knowledge management combining Zettelkasten with knowledge graphs"""
 
 # Package version - updated by release automation
-__version__ = "0.18.5"
+__version__ = "0.20.3"
 
 # API version for FastAPI - independent of package version
 __api_version__ = "v0"

src/basic_memory/alembic/versions/j3d4e5f6g7h8_rename_entity_type_to_note_type.py

@@ -22,10 +22,7 @@ def table_exists(connection, table_name: str) -> bool:
     """Check if a table exists (idempotent migration support)."""
     if connection.dialect.name == "postgresql":
         result = connection.execute(
-            text(
-                "SELECT 1 FROM information_schema.tables "
-                "WHERE table_name = :table_name"
-            ),
+            text("SELECT 1 FROM information_schema.tables WHERE table_name = :table_name"),
             {"table_name": table_name},
         )
         return result.fetchone() is not None

src/basic_memory/api/app.py

@@ -25,6 +25,7 @@ from basic_memory.api.v2.routers.project_router import (
     list_projects,
     synchronize_projects,
 )
+from basic_memory import telemetry
 from basic_memory.config import init_api_logging
 from basic_memory.services.exceptions import EntityAlreadyExistsError
 from basic_memory.services.initialization import initialize_app
@@ -43,30 +44,39 @@ async def lifespan(app: FastAPI):  # pragma: no cover
     set_container(container)
     app.state.container = container
 
-    logger.info(f"Starting Basic Memory API (mode={container.mode.name})")
+    with telemetry.operation(
+        "api.lifecycle.startup",
+        entrypoint="api",
+        mode=container.mode.name.lower(),
+    ):
+        logger.info(f"Starting Basic Memory API (mode={container.mode.name})")
 
-    await initialize_app(container.config)
+        await initialize_app(container.config)
 
-    # Cache database connections in app state for performance
-    logger.info("Initializing database and caching connections...")
-    engine, session_maker = await container.init_database()
-    app.state.engine = engine
-    app.state.session_maker = session_maker
-    logger.info("Database connections cached in app state")
+        # Cache database connections in app state for performance
+        logger.info("Initializing database and caching connections...")
+        engine, session_maker = await container.init_database()
+        app.state.engine = engine
+        app.state.session_maker = session_maker
+        logger.info("Database connections cached in app state")
 
-    # Create and start sync coordinator (lifecycle centralized in coordinator)
-    sync_coordinator = container.create_sync_coordinator()
-    await sync_coordinator.start()
-    app.state.sync_coordinator = sync_coordinator
+        # Create and start sync coordinator (lifecycle centralized in coordinator)
+        sync_coordinator = container.create_sync_coordinator()
+        await sync_coordinator.start()
+        app.state.sync_coordinator = sync_coordinator
 
     # Proceed with startup
     yield
 
     # Shutdown - coordinator handles clean task cancellation
-    logger.info("Shutting down Basic Memory API")
-    await sync_coordinator.stop()
-
-    await container.shutdown_database()
+    with telemetry.operation(
+        "api.lifecycle.shutdown",
+        entrypoint="api",
+        mode=container.mode.name.lower(),
+    ):
+        logger.info("Shutting down Basic Memory API")
+        await sync_coordinator.stop()
+        await container.shutdown_database()
 
 
 # Initialize FastAPI app

src/basic_memory/api/v2/routers/knowledge_router.py

@@ -13,6 +13,7 @@ Key improvements:
 from fastapi import APIRouter, HTTPException, BackgroundTasks, Depends, Response, Path, Query
 from loguru import logger
 
+from basic_memory import telemetry
 from basic_memory.deps import (
     EntityServiceV2ExternalDep,
     SearchServiceV2ExternalDep,
@@ -20,6 +21,7 @@ from basic_memory.deps import (
     ProjectConfigV2ExternalDep,
     AppConfigDep,
     EntityRepositoryV2ExternalDep,
+    RelationRepositoryV2ExternalDep,
     ProjectExternalIdPathDep,
     TaskSchedulerDep,
     FileServiceV2ExternalDep,
@@ -31,6 +33,9 @@ from basic_memory.schemas.v2 import (
     EntityResolveRequest,
     EntityResolveResponse,
     EntityResponseV2,
+    GraphEdge,
+    GraphNode,
+    GraphResponse,
     MoveEntityRequestV2,
     MoveDirectoryRequestV2,
     DeleteDirectoryRequestV2,
@@ -56,6 +61,50 @@ def _schedule_vector_sync_if_enabled(
         )
 
 
+## Graph endpoint
+
+
+@router.get("/graph", response_model=GraphResponse)
+async def get_graph(
+    project_id: ProjectExternalIdPathDep,
+    entity_repository: EntityRepositoryV2ExternalDep,
+    relation_repository: RelationRepositoryV2ExternalDep,
+) -> GraphResponse:
+    """Return all entities and resolved relations for knowledge graph visualization.
+
+    Returns a flat node/edge structure optimized for rendering with graph libraries.
+    Only includes resolved relations (where to_id is not null).
+    """
+    logger.info("API v2 request: get_graph")
+
+    # Fetch all entities for this project
+    entities = await entity_repository.find_all(use_load_options=False)
+    nodes = [
+        GraphNode(
+            external_id=entity.external_id,
+            title=entity.title,
+            note_type=entity.note_type,
+            file_path=entity.file_path,
+        )
+        for entity in entities
+    ]
+
+    # Fetch all resolved relations (to_id is not null) with eager-loaded entities
+    relations = await relation_repository.find_all()
+    edges = [
+        GraphEdge(
+            from_id=relation.from_entity.external_id,
+            to_id=relation.to_entity.external_id,
+            relation_type=relation.relation_type,
+        )
+        for relation in relations
+        if relation.to_entity is not None
+    ]
+
+    logger.info(f"API v2 response: graph with {len(nodes)} nodes and {len(edges)} edges")
+    return GraphResponse(nodes=nodes, edges=edges)
+
+
 ## Resolution endpoint
 
 
@@ -94,47 +143,66 @@ async def resolve_identifier(
             "resolution_method": "permalink"
         }
     """
-    logger.info(f"API v2 request: resolve_identifier for '{data.identifier}'")
+    with telemetry.operation(
+        "api.request.knowledge.resolve_entity",
+        entrypoint="api",
+        domain="knowledge",
+        action="resolve_entity",
+    ):
+        logger.info(f"API v2 request: resolve_identifier for '{data.identifier}'")
 
-    # Try to resolve by external_id first
-    entity = await entity_repository.get_by_external_id(data.identifier)
-    resolution_method = "external_id" if entity else "search"
+        with telemetry.scope(
+            "api.knowledge.resolve_entity.lookup_entity",
+            domain="knowledge",
+            action="resolve_entity",
+            phase="lookup_entity",
+        ):
+            entity = await entity_repository.get_by_external_id(data.identifier)
+        resolution_method = "external_id" if entity else "search"
 
-    # If not found by external_id, try other resolution methods
-    # Pass source_path for context-aware resolution (prefers notes closer to source)
-    # Pass strict to control fuzzy search fallback (default False allows fuzzy matching)
-    if not entity:
-        entity = await link_resolver.resolve_link(
-            data.identifier, source_path=data.source_path, strict=data.strict
+        if not entity:
+            with telemetry.scope(
+                "api.knowledge.resolve_entity.resolve_link",
+                domain="knowledge",
+                action="resolve_entity",
+                phase="resolve_link",
+            ):
+                entity = await link_resolver.resolve_link(
+                    data.identifier, source_path=data.source_path, strict=data.strict
+                )
+            if entity:
+                if entity.permalink == data.identifier:
+                    resolution_method = "permalink"
+                elif entity.title == data.identifier:
+                    resolution_method = "title"
+                elif entity.file_path == data.identifier:
+                    resolution_method = "path"
+                else:
+                    resolution_method = "search"
+
+        if not entity:
+            raise HTTPException(status_code=404, detail=f"Entity not found: '{data.identifier}'")
+
+        with telemetry.scope(
+            "api.knowledge.resolve_entity.shape_response",
+            domain="knowledge",
+            action="resolve_entity",
+            phase="shape_response",
+        ):
+            result = EntityResolveResponse(
+                external_id=entity.external_id,
+                entity_id=entity.id,
+                permalink=entity.permalink,
+                file_path=entity.file_path,
+                title=entity.title,
+                resolution_method=resolution_method,
+            )
+
+        logger.debug(
+            f"API v2 response: resolved '{data.identifier}' to external_id={result.external_id} via {resolution_method}"
         )
-        if entity:
-            # Determine resolution method
-            if entity.permalink == data.identifier:
-                resolution_method = "permalink"
-            elif entity.title == data.identifier:
-                resolution_method = "title"
-            elif entity.file_path == data.identifier:
-                resolution_method = "path"
-            else:
-                resolution_method = "search"
 
-    if not entity:
-        raise HTTPException(status_code=404, detail=f"Entity not found: '{data.identifier}'")
-
-    result = EntityResolveResponse(
-        external_id=entity.external_id,
-        entity_id=entity.id,
-        permalink=entity.permalink,
-        file_path=entity.file_path,
-        title=entity.title,
-        resolution_method=resolution_method,
-    )
-
-    logger.info(
-        f"API v2 response: resolved '{data.identifier}' to external_id={result.external_id} via {resolution_method}"
-    )
-
-    return result
+        return result
 
 
 ## Read endpoints
@@ -160,18 +228,36 @@ async def get_entity_by_id(
     Raises:
         HTTPException: 404 if entity not found
     """
-    logger.info(f"API v2 request: get_entity_by_id entity_id={entity_id}")
+    with telemetry.operation(
+        "api.request.knowledge.get_entity",
+        entrypoint="api",
+        domain="knowledge",
+        action="get_entity",
+    ):
+        logger.info(f"API v2 request: get_entity_by_id entity_id={entity_id}")
 
-    entity = await entity_repository.get_by_external_id(entity_id)
-    if not entity:
-        raise HTTPException(
-            status_code=404, detail=f"Entity with external_id '{entity_id}' not found"
-        )
+        with telemetry.scope(
+            "api.knowledge.get_entity.load_entity",
+            domain="knowledge",
+            action="get_entity",
+            phase="load_entity",
+        ):
+            entity = await entity_repository.get_by_external_id(entity_id)
+        if not entity:
+            raise HTTPException(
+                status_code=404, detail=f"Entity with external_id '{entity_id}' not found"
+            )
 
-    result = EntityResponseV2.model_validate(entity)
-    logger.info(f"API v2 response: external_id={entity_id}, title='{result.title}'")
+        with telemetry.scope(
+            "api.knowledge.get_entity.shape_response",
+            domain="knowledge",
+            action="get_entity",
+            phase="shape_response",
+        ):
+            result = EntityResponseV2.model_validate(entity)
+        logger.info(f"API v2 response: external_id={entity_id}, title='{result.title}'")
 
-    return result
+        return result
 
 
 ## Create endpoints
@@ -200,39 +286,92 @@ async def create_entity(
     Returns:
         Created entity with generated external_id (UUID) and file content
     """
-    logger.info(
-        "API v2 request", endpoint="create_entity", note_type=data.note_type, title=data.title
-    )
-
-    if fast:
-        entity = await entity_service.fast_write_entity(data)
-        task_scheduler.schedule(
-            "reindex_entity",
-            entity_id=entity.id,
-            project_id=project_id,
-        )
-    else:
-        entity = await entity_service.create_entity(data)
-        await search_service.index_entity(entity)
-        _schedule_vector_sync_if_enabled(
-            task_scheduler=task_scheduler,
-            app_config=app_config,
-            entity_id=entity.id,
-            project_id=project_id,
+    with telemetry.operation(
+        "api.request.knowledge.create_entity",
+        entrypoint="api",
+        domain="knowledge",
+        action="create_entity",
+        fast=fast,
+    ):
+        logger.info(
+            "API v2 request", endpoint="create_entity", note_type=data.note_type, title=data.title
         )
 
-    result = EntityResponseV2.model_validate(entity)
-    if fast:
-        result = result.model_copy(update={"observations": [], "relations": []})
+        with telemetry.scope(
+            "api.knowledge.create_entity.write_entity",
+            domain="knowledge",
+            action="create_entity",
+            phase="write_entity",
+            fast=fast,
+        ):
+            if fast:
+                entity = await entity_service.fast_write_entity(data)
+                written_content = None
+                search_content = None
+            else:
+                write_result = await entity_service.create_entity_with_content(data)
+                entity = write_result.entity
+                written_content = write_result.content
+                search_content = write_result.search_content
 
-    # Always read and return file content
-    content = await file_service.read_file_content(entity.file_path)
-    result = result.model_copy(update={"content": content})
+        if fast:
+            with telemetry.scope(
+                "api.knowledge.create_entity.enqueue_reindex",
+                domain="knowledge",
+                action="create_entity",
+                phase="enqueue_reindex",
+                fast=fast,
+            ):
+                task_scheduler.schedule(
+                    "reindex_entity",
+                    entity_id=entity.id,
+                    project_id=project_id,
+                )
+        else:
+            with telemetry.scope(
+                "api.knowledge.create_entity.search_index",
+                domain="knowledge",
+                action="create_entity",
+                phase="search_index",
+            ):
+                await search_service.index_entity(entity, content=search_content)
+            with telemetry.scope(
+                "api.knowledge.create_entity.vector_sync",
+                domain="knowledge",
+                action="create_entity",
+                phase="vector_sync",
+            ):
+                _schedule_vector_sync_if_enabled(
+                    task_scheduler=task_scheduler,
+                    app_config=app_config,
+                    entity_id=entity.id,
+                    project_id=project_id,
+                )
 
-    logger.info(
-        f"API v2 response: endpoint='create_entity' external_id={entity.external_id}, title={result.title}, permalink={result.permalink}, status_code=201"
-    )
-    return result
+        result = EntityResponseV2.model_validate(entity)
+        if fast:
+            result = result.model_copy(update={"observations": [], "relations": []})
+
+        with telemetry.scope(
+            "api.knowledge.create_entity.read_content",
+            domain="knowledge",
+            action="create_entity",
+            phase="read_content",
+            source="file" if fast else "memory",
+        ):
+            if fast:
+                content = await file_service.read_file_content(entity.file_path)
+            else:
+                # Non-fast writes already captured the markdown in memory. Reuse it here
+                # instead of re-reading the file; format_on_save is the one config that can
+                # still make the persisted file diverge because write_file only returns a checksum.
+                content = written_content
+        result = result.model_copy(update={"content": content})
+
+        logger.info(
+            f"API v2 response: endpoint='create_entity' external_id={entity.external_id}, title={result.title}, permalink={result.permalink}, status_code=201"
+        )
+        return result
 
 
 ## Update endpoints
@@ -267,61 +406,121 @@ async def update_entity_by_id(
     Returns:
         Updated entity with file content
     """
-    logger.info(f"API v2 request: update_entity_by_id entity_id={entity_id}")
+    with telemetry.operation(
+        "api.request.knowledge.update_entity",
+        entrypoint="api",
+        domain="knowledge",
+        action="update_entity",
+        fast=fast,
+    ):
+        logger.info(f"API v2 request: update_entity_by_id entity_id={entity_id}")
 
-    # Check if entity exists (external_id is the source of truth for v2)
-    existing = await entity_repository.get_by_external_id(entity_id)
-    created = existing is None
+        with telemetry.scope(
+            "api.knowledge.update_entity.load_entity",
+            domain="knowledge",
+            action="update_entity",
+            phase="load_entity",
+        ):
+            existing = await entity_repository.get_by_external_id(entity_id)
+        created = existing is None
 
-    if fast:
-        entity = await entity_service.fast_write_entity(data, external_id=entity_id)
-        response.status_code = 200 if existing else 201
-        task_scheduler.schedule(
-            "reindex_entity",
-            entity_id=entity.id,
-            project_id=project_id,
-            resolve_relations=created,
-        )
-    else:
-        if existing:
-            # Update the existing entity in-place to avoid path-based duplication
-            entity = await entity_service.update_entity(existing, data)
-            response.status_code = 200
-        else:
-            # Create new entity, then bind external_id to the requested UUID
-            entity = await entity_service.create_entity(data)
-            if entity.external_id != entity_id:
-                entity = await entity_repository.update(
-                    entity.id,
-                    {"external_id": entity_id},
+        with telemetry.scope(
+            "api.knowledge.update_entity.write_entity",
+            domain="knowledge",
+            action="update_entity",
+            phase="write_entity",
+            fast=fast,
+        ):
+            if fast:
+                entity = await entity_service.fast_write_entity(data, external_id=entity_id)
+                written_content = None
+                search_content = None
+                response.status_code = 200 if existing else 201
+            else:
+                if existing:
+                    write_result = await entity_service.update_entity_with_content(existing, data)
+                    entity = write_result.entity
+                    written_content = write_result.content
+                    search_content = write_result.search_content
+                    response.status_code = 200
+                else:
+                    write_result = await entity_service.create_entity_with_content(data)
+                    entity = write_result.entity
+                    written_content = write_result.content
+                    search_content = write_result.search_content
+                    if entity.external_id != entity_id:
+                        entity = await entity_repository.update(
+                            entity.id,
+                            {"external_id": entity_id},
+                        )
+                        # external_id fixup only changes the DB row. The file content is unchanged,
+                        # so the markdown captured during the write remains valid downstream.
+                        if not entity:
+                            raise HTTPException(
+                                status_code=404,
+                                detail=f"Entity with external_id '{entity_id}' not found",
+                            )
+                    response.status_code = 201
+
+        if fast:
+            with telemetry.scope(
+                "api.knowledge.update_entity.enqueue_reindex",
+                domain="knowledge",
+                action="update_entity",
+                phase="enqueue_reindex",
+                fast=fast,
+            ):
+                task_scheduler.schedule(
+                    "reindex_entity",
+                    entity_id=entity.id,
+                    project_id=project_id,
+                    resolve_relations=created,
+                )
+        else:
+            with telemetry.scope(
+                "api.knowledge.update_entity.search_index",
+                domain="knowledge",
+                action="update_entity",
+                phase="search_index",
+            ):
+                await search_service.index_entity(entity, content=search_content)
+            with telemetry.scope(
+                "api.knowledge.update_entity.vector_sync",
+                domain="knowledge",
+                action="update_entity",
+                phase="vector_sync",
+            ):
+                _schedule_vector_sync_if_enabled(
+                    task_scheduler=task_scheduler,
+                    app_config=app_config,
+                    entity_id=entity.id,
+                    project_id=project_id,
                 )
-                if not entity:
-                    raise HTTPException(
-                        status_code=404,
-                        detail=f"Entity with external_id '{entity_id}' not found",
-                    )
-            response.status_code = 201
 
-        await search_service.index_entity(entity)
-        _schedule_vector_sync_if_enabled(
-            task_scheduler=task_scheduler,
-            app_config=app_config,
-            entity_id=entity.id,
-            project_id=project_id,
+        result = EntityResponseV2.model_validate(entity)
+        if fast:
+            result = result.model_copy(update={"observations": [], "relations": []})
+
+        with telemetry.scope(
+            "api.knowledge.update_entity.read_content",
+            domain="knowledge",
+            action="update_entity",
+            phase="read_content",
+            source="file" if fast else "memory",
+        ):
+            if fast:
+                content = await file_service.read_file_content(entity.file_path)
+            else:
+                # Non-fast writes already captured the markdown in memory. Reuse it here
+                # instead of re-reading the file; format_on_save is the one config that can
+                # still make the persisted file diverge because write_file only returns a checksum.
+                content = written_content
+        result = result.model_copy(update={"content": content})
+
+        logger.info(
+            f"API v2 response: external_id={entity_id}, created={created}, status_code={response.status_code}"
         )
-
-    result = EntityResponseV2.model_validate(entity)
-    if fast:
-        result = result.model_copy(update={"observations": [], "relations": []})
-
-    # Always read and return file content
-    content = await file_service.read_file_content(entity.file_path)
-    result = result.model_copy(update={"content": content})
-
-    logger.info(
-        f"API v2 response: external_id={entity_id}, created={created}, status_code={response.status_code}"
-    )
-    return result
+        return result
 
 
 @router.patch("/entities/{entity_id}", response_model=EntityResponseV2)
@@ -353,69 +552,125 @@ async def edit_entity_by_id(
     Raises:
         HTTPException: 404 if entity not found, 400 if edit fails
     """
-    logger.info(
-        f"API v2 request: edit_entity_by_id entity_id={entity_id}, operation='{data.operation}'"
-    )
-
-    # Verify entity exists
-    entity = await entity_repository.get_by_external_id(entity_id)
-    if not entity:  # pragma: no cover
-        raise HTTPException(
-            status_code=404, detail=f"Entity with external_id '{entity_id}' not found"
-        )
-
-    try:
-        if fast:
-            updated_entity = await entity_service.fast_edit_entity(
-                entity=entity,
-                operation=data.operation,
-                content=data.content,
-                section=data.section,
-                find_text=data.find_text,
-                expected_replacements=data.expected_replacements,
-            )
-            task_scheduler.schedule(
-                "reindex_entity",
-                entity_id=updated_entity.id,
-                project_id=project_id,
-            )
-        else:
-            # Edit using the entity's permalink or path
-            identifier = entity.permalink or entity.file_path
-            updated_entity = await entity_service.edit_entity(
-                identifier=identifier,
-                operation=data.operation,
-                content=data.content,
-                section=data.section,
-                find_text=data.find_text,
-                expected_replacements=data.expected_replacements,
-            )
-
-            await search_service.index_entity(updated_entity)
-            _schedule_vector_sync_if_enabled(
-                task_scheduler=task_scheduler,
-                app_config=app_config,
-                entity_id=updated_entity.id,
-                project_id=project_id,
-            )
-
-        result = EntityResponseV2.model_validate(updated_entity)
-        if fast:
-            result = result.model_copy(update={"observations": [], "relations": []})
-
-        # Always read and return file content
-        content = await file_service.read_file_content(updated_entity.file_path)
-        result = result.model_copy(update={"content": content})
-
+    with telemetry.operation(
+        "api.request.knowledge.edit_entity",
+        entrypoint="api",
+        domain="knowledge",
+        action="edit_entity",
+        fast=fast,
+    ):
         logger.info(
-            f"API v2 response: external_id={entity_id}, operation='{data.operation}', status_code=200"
+            f"API v2 request: edit_entity_by_id entity_id={entity_id}, operation='{data.operation}'"
         )
 
-        return result
+        with telemetry.scope(
+            "api.knowledge.edit_entity.load_entity",
+            domain="knowledge",
+            action="edit_entity",
+            phase="load_entity",
+        ):
+            entity = await entity_repository.get_by_external_id(entity_id)
+        if not entity:  # pragma: no cover
+            raise HTTPException(
+                status_code=404, detail=f"Entity with external_id '{entity_id}' not found"
+            )
 
-    except Exception as e:
-        logger.error(f"Error editing entity {entity_id}: {e}")
-        raise HTTPException(status_code=400, detail=str(e))
+        try:
+            with telemetry.scope(
+                "api.knowledge.edit_entity.write_entity",
+                domain="knowledge",
+                action="edit_entity",
+                phase="write_entity",
+                fast=fast,
+            ):
+                if fast:
+                    updated_entity = await entity_service.fast_edit_entity(
+                        entity=entity,
+                        operation=data.operation,
+                        content=data.content,
+                        section=data.section,
+                        find_text=data.find_text,
+                        expected_replacements=data.expected_replacements,
+                    )
+                    written_content = None
+                    search_content = None
+                else:
+                    identifier = entity.permalink or entity.file_path
+                    write_result = await entity_service.edit_entity_with_content(
+                        identifier=identifier,
+                        operation=data.operation,
+                        content=data.content,
+                        section=data.section,
+                        find_text=data.find_text,
+                        expected_replacements=data.expected_replacements,
+                    )
+                    updated_entity = write_result.entity
+                    written_content = write_result.content
+                    search_content = write_result.search_content
+
+            if fast:
+                with telemetry.scope(
+                    "api.knowledge.edit_entity.enqueue_reindex",
+                    domain="knowledge",
+                    action="edit_entity",
+                    phase="enqueue_reindex",
+                    fast=fast,
+                ):
+                    task_scheduler.schedule(
+                        "reindex_entity",
+                        entity_id=updated_entity.id,
+                        project_id=project_id,
+                    )
+            else:
+                with telemetry.scope(
+                    "api.knowledge.edit_entity.search_index",
+                    domain="knowledge",
+                    action="edit_entity",
+                    phase="search_index",
+                ):
+                    await search_service.index_entity(updated_entity, content=search_content)
+                with telemetry.scope(
+                    "api.knowledge.edit_entity.vector_sync",
+                    domain="knowledge",
+                    action="edit_entity",
+                    phase="vector_sync",
+                ):
+                    _schedule_vector_sync_if_enabled(
+                        task_scheduler=task_scheduler,
+                        app_config=app_config,
+                        entity_id=updated_entity.id,
+                        project_id=project_id,
+                    )
+
+            result = EntityResponseV2.model_validate(updated_entity)
+            if fast:
+                result = result.model_copy(update={"observations": [], "relations": []})
+
+            with telemetry.scope(
+                "api.knowledge.edit_entity.read_content",
+                domain="knowledge",
+                action="edit_entity",
+                phase="read_content",
+                source="file" if fast else "memory",
+            ):
+                if fast:
+                    content = await file_service.read_file_content(updated_entity.file_path)
+                else:
+                    # Non-fast writes already captured the markdown in memory. Reuse it here
+                    # instead of re-reading the file; format_on_save is the one config that can
+                    # still make the persisted file diverge because write_file only returns a checksum.
+                    content = written_content
+            result = result.model_copy(update={"content": content})
+
+            logger.info(
+                f"API v2 response: external_id={entity_id}, operation='{data.operation}', status_code=200"
+            )
+
+            return result
+
+        except Exception as e:
+            logger.error(f"Error editing entity {entity_id}: {e}")
+            raise HTTPException(status_code=400, detail=str(e))
 
 
 ## Delete endpoints

src/basic_memory/api/v2/routers/memory_router.py

@@ -9,6 +9,7 @@ from typing import Annotated, Optional
 from fastapi import APIRouter, Query, Path
 from loguru import logger
 
+from basic_memory import telemetry
 from basic_memory.deps import ContextServiceV2ExternalDep, EntityRepositoryV2ExternalDep
 from basic_memory.schemas.base import TimeFrame, parse_timeframe
 from basic_memory.schemas.memory import (
@@ -50,30 +51,55 @@ async def recent(
     Returns:
         GraphContext with recent activity and related entities
     """
-    # return all types by default
-    types = (
-        [SearchItemType.ENTITY, SearchItemType.RELATION, SearchItemType.OBSERVATION]
-        if not type
-        else type
-    )
+    with telemetry.operation(
+        "api.request.memory.recent_activity",
+        entrypoint="api",
+        domain="memory",
+        action="recent_activity",
+        page=page,
+        page_size=page_size,
+    ):
+        types = (
+            [SearchItemType.ENTITY, SearchItemType.RELATION, SearchItemType.OBSERVATION]
+            if not type
+            else type
+        )
 
-    logger.debug(
-        f"V2 Getting recent context for project {project_id}: `{types}` depth: `{depth}` timeframe: `{timeframe}` page: `{page}` page_size: `{page_size}` max_related: `{max_related}`"
-    )
-    # Parse timeframe
-    since = parse_timeframe(timeframe)
-    limit = page_size
-    offset = (page - 1) * page_size
+        logger.debug(
+            f"V2 Getting recent context for project {project_id}: `{types}` depth: `{depth}` timeframe: `{timeframe}` page: `{page}` page_size: `{page_size}` max_related: `{max_related}`"
+        )
+        since = parse_timeframe(timeframe)
+        limit = page_size
+        offset = (page - 1) * page_size
 
-    # Build context
-    context = await context_service.build_context(
-        types=types, depth=depth, since=since, limit=limit, offset=offset, max_related=max_related
-    )
-    recent_context = await to_graph_context(
-        context, entity_repository=entity_repository, page=page, page_size=page_size
-    )
-    logger.debug(f"V2 Recent context: {recent_context.model_dump_json()}")
-    return recent_context
+        with telemetry.scope(
+            "api.memory.recent_activity.build_context",
+            domain="memory",
+            action="recent_activity",
+            phase="build_context",
+            page=page,
+            page_size=page_size,
+        ):
+            context = await context_service.build_context(
+                types=types,
+                depth=depth,
+                since=since,
+                limit=limit,
+                offset=offset,
+                max_related=max_related,
+            )
+        with telemetry.scope(
+            "api.memory.recent_activity.shape_response",
+            domain="memory",
+            action="recent_activity",
+            phase="shape_response",
+            result_count=len(context.results),
+        ):
+            recent_context = await to_graph_context(
+                context, entity_repository=entity_repository, page=page, page_size=page_size
+            )
+        logger.debug(f"V2 Recent context: {recent_context.model_dump_json()}")
+        return recent_context
 
 
 # get_memory_context needs to be declared last so other paths can match
@@ -111,20 +137,46 @@ async def get_memory_context(
     Returns:
         GraphContext with the entity and its related context
     """
-    logger.debug(
-        f"V2 Getting context for project {project_id}, URI: `{uri}` depth: `{depth}` timeframe: `{timeframe}` page: `{page}` page_size: `{page_size}` max_related: `{max_related}`"
-    )
-    memory_url = normalize_memory_url(uri)
+    with telemetry.operation(
+        "api.request.memory.build_context",
+        entrypoint="api",
+        domain="memory",
+        action="build_context",
+        page=page,
+        page_size=page_size,
+    ):
+        logger.debug(
+            f"V2 Getting context for project {project_id}, URI: `{uri}` depth: `{depth}` timeframe: `{timeframe}` page: `{page}` page_size: `{page_size}` max_related: `{max_related}`"
+        )
+        memory_url = normalize_memory_url(uri)
 
-    # Parse timeframe
-    since = parse_timeframe(timeframe) if timeframe else None
-    limit = page_size
-    offset = (page - 1) * page_size
+        since = parse_timeframe(timeframe) if timeframe else None
+        limit = page_size
+        offset = (page - 1) * page_size
 
-    # Build context
-    context = await context_service.build_context(
-        memory_url, depth=depth, since=since, limit=limit, offset=offset, max_related=max_related
-    )
-    return await to_graph_context(
-        context, entity_repository=entity_repository, page=page, page_size=page_size
-    )
+        with telemetry.scope(
+            "api.memory.build_context.build_context",
+            domain="memory",
+            action="build_context",
+            phase="build_context",
+            page=page,
+            page_size=page_size,
+        ):
+            context = await context_service.build_context(
+                memory_url,
+                depth=depth,
+                since=since,
+                limit=limit,
+                offset=offset,
+                max_related=max_related,
+            )
+        with telemetry.scope(
+            "api.memory.build_context.shape_response",
+            domain="memory",
+            action="build_context",
+            phase="shape_response",
+            result_count=len(context.results),
+        ):
+            return await to_graph_context(
+                context, entity_repository=entity_repository, page=page, page_size=page_size
+            )

src/basic_memory/api/v2/routers/project_router.py

@@ -48,7 +48,7 @@ async def list_projects(
         A list of all projects with metadata
     """
     projects = await project_service.list_projects()
-    default_project = project_service.default_project
+    default_project = await project_service.get_default_project_name()
 
     project_items = [
         ProjectItem(

src/basic_memory/api/v2/routers/resource_router.py

@@ -15,6 +15,7 @@ from pathlib import Path as PathLib
 from fastapi import APIRouter, HTTPException, Response, Path
 from loguru import logger
 
+from basic_memory import telemetry
 from basic_memory.deps import (
     ProjectConfigV2ExternalDep,
     FileServiceV2ExternalDep,
@@ -55,36 +56,62 @@ async def get_resource_content(
     Raises:
         HTTPException: 404 if entity or file not found
     """
-    logger.debug(f"V2 Getting content for project {project_id}, entity_id: {entity_id}")
+    with telemetry.operation(
+        "api.request.resource.get_content",
+        entrypoint="api",
+        domain="resource",
+        action="get_content",
+    ):
+        logger.debug(f"V2 Getting content for project {project_id}, entity_id: {entity_id}")
 
-    # Get entity by external_id
-    entity = await entity_repository.get_by_external_id(entity_id)
-    if not entity:
-        raise HTTPException(status_code=404, detail=f"Entity {entity_id} not found")
+        with telemetry.scope(
+            "api.resource.get_content.load_entity",
+            domain="resource",
+            action="get_content",
+            phase="load_entity",
+        ):
+            entity = await entity_repository.get_by_external_id(entity_id)
+        if not entity:
+            raise HTTPException(status_code=404, detail=f"Entity {entity_id} not found")
 
-    # Validate entity file path to prevent path traversal
-    project_path = PathLib(config.home)
-    if not validate_project_path(entity.file_path, project_path):
-        logger.error(  # pragma: no cover
-            f"Invalid file path in entity {entity.id}: {entity.file_path}"
-        )
-        raise HTTPException(  # pragma: no cover
-            status_code=500,
-            detail="Entity contains invalid file path",
-        )
+        with telemetry.scope(
+            "api.resource.get_content.validate_path",
+            domain="resource",
+            action="get_content",
+            phase="validate_path",
+        ):
+            project_path = PathLib(config.home)
+            if not validate_project_path(entity.file_path, project_path):
+                logger.error(  # pragma: no cover
+                    f"Invalid file path in entity {entity.id}: {entity.file_path}"
+                )
+                raise HTTPException(  # pragma: no cover
+                    status_code=500,
+                    detail="Entity contains invalid file path",
+                )
 
-    # Check file exists via file_service (for cloud compatibility)
-    if not await file_service.exists(entity.file_path):
-        raise HTTPException(  # pragma: no cover
-            status_code=404,
-            detail=f"File not found: {entity.file_path}",
-        )
+        with telemetry.scope(
+            "api.resource.get_content.ensure_exists",
+            domain="resource",
+            action="get_content",
+            phase="ensure_exists",
+        ):
+            if not await file_service.exists(entity.file_path):
+                raise HTTPException(  # pragma: no cover
+                    status_code=404,
+                    detail=f"File not found: {entity.file_path}",
+                )
 
-    # Read content via file_service as bytes (works with both local and S3)
-    content = await file_service.read_file_bytes(entity.file_path)
-    content_type = file_service.content_type(entity.file_path)
+        with telemetry.scope(
+            "api.resource.get_content.read_content",
+            domain="resource",
+            action="get_content",
+            phase="read_content",
+        ):
+            content = await file_service.read_file_bytes(entity.file_path)
+            content_type = file_service.content_type(entity.file_path)
 
-    return Response(content=content, media_type=content_type)
+        return Response(content=content, media_type=content_type)
 
 
 @router.post("", response_model=ResourceResponse)
@@ -112,74 +139,94 @@ async def create_resource(
     Raises:
         HTTPException: 400 for invalid file paths, 409 if file already exists
     """
-    try:
-        # Validate path to prevent path traversal attacks
-        project_path = PathLib(config.home)
-        if not validate_project_path(data.file_path, project_path):
-            logger.warning(
-                f"Invalid file path attempted: {data.file_path} in project {config.name}"
+    with telemetry.operation(
+        "api.request.resource.create",
+        entrypoint="api",
+        domain="resource",
+        action="create",
+    ):
+        try:
+            # Validate path to prevent path traversal attacks
+            project_path = PathLib(config.home)
+            if not validate_project_path(data.file_path, project_path):
+                logger.warning(
+                    f"Invalid file path attempted: {data.file_path} in project {config.name}"
+                )
+                raise HTTPException(
+                    status_code=400,
+                    detail=f"Invalid file path: {data.file_path}. "
+                    "Path must be relative and stay within project boundaries.",
+                )
+
+            existing_entity = await entity_repository.get_by_file_path(data.file_path)
+            if existing_entity:
+                raise HTTPException(
+                    status_code=409,
+                    detail=f"Resource already exists at {data.file_path} with entity_id {existing_entity.external_id}. "
+                    f"Use PUT /resource/{existing_entity.external_id} to update it.",
+                )
+
+            with telemetry.scope(
+                "api.resource.create.write_file",
+                domain="resource",
+                action="create",
+                phase="write_file",
+            ):
+                await file_service.ensure_directory(PathLib(data.file_path).parent)
+                checksum = await file_service.write_file(data.file_path, data.content)
+
+            with telemetry.scope(
+                "api.resource.create.read_metadata",
+                domain="resource",
+                action="create",
+                phase="read_metadata",
+            ):
+                file_metadata = await file_service.get_file_metadata(data.file_path)
+
+            file_name = PathLib(data.file_path).name
+            content_type = file_service.content_type(data.file_path)
+            note_type = "canvas" if data.file_path.endswith(".canvas") else "file"
+
+            entity = EntityModel(
+                external_id=str(uuid.uuid4()),
+                title=file_name,
+                note_type=note_type,
+                content_type=content_type,
+                file_path=data.file_path,
+                checksum=checksum,
+                created_at=file_metadata.created_at,
+                updated_at=file_metadata.modified_at,
             )
-            raise HTTPException(
-                status_code=400,
-                detail=f"Invalid file path: {data.file_path}. "
-                "Path must be relative and stay within project boundaries.",
+            with telemetry.scope(
+                "api.resource.create.upsert_entity",
+                domain="resource",
+                action="create",
+                phase="upsert_entity",
+            ):
+                entity = await entity_repository.add(entity)
+
+            with telemetry.scope(
+                "api.resource.create.search_index",
+                domain="resource",
+                action="create",
+                phase="search_index",
+            ):
+                await search_service.index_entity(entity)  # pyright: ignore
+
+            return ResourceResponse(
+                entity_id=entity.id,
+                external_id=entity.external_id,
+                file_path=data.file_path,
+                checksum=checksum,
+                size=file_metadata.size,
+                created_at=file_metadata.created_at.timestamp(),
+                modified_at=file_metadata.modified_at.timestamp(),
             )
-
-        # Check if entity already exists
-        existing_entity = await entity_repository.get_by_file_path(data.file_path)
-        if existing_entity:
-            raise HTTPException(
-                status_code=409,
-                detail=f"Resource already exists at {data.file_path} with entity_id {existing_entity.external_id}. "
-                f"Use PUT /resource/{existing_entity.external_id} to update it.",
-            )
-
-        # Cloud compatibility: avoid assuming a local filesystem path.
-        # Delegate directory creation + writes to FileService (local or S3).
-        await file_service.ensure_directory(PathLib(data.file_path).parent)
-        checksum = await file_service.write_file(data.file_path, data.content)
-
-        # Get file info
-        file_metadata = await file_service.get_file_metadata(data.file_path)
-
-        # Determine file details
-        file_name = PathLib(data.file_path).name
-        content_type = file_service.content_type(data.file_path)
-        note_type = "canvas" if data.file_path.endswith(".canvas") else "file"
-
-        # Create a new entity model
-        # Explicitly set external_id to ensure NOT NULL constraint is satisfied (fixes #512)
-        entity = EntityModel(
-            external_id=str(uuid.uuid4()),
-            title=file_name,
-            note_type=note_type,
-            content_type=content_type,
-            file_path=data.file_path,
-            checksum=checksum,
-            created_at=file_metadata.created_at,
-            updated_at=file_metadata.modified_at,
-        )
-        entity = await entity_repository.add(entity)
-
-        # Index the file for search
-        await search_service.index_entity(entity)  # pyright: ignore
-
-        # Return success response
-        return ResourceResponse(
-            entity_id=entity.id,
-            external_id=entity.external_id,
-            file_path=data.file_path,
-            checksum=checksum,
-            size=file_metadata.size,
-            created_at=file_metadata.created_at.timestamp(),
-            modified_at=file_metadata.modified_at.timestamp(),
-        )
-    except HTTPException:
-        # Re-raise HTTP exceptions without wrapping
-        raise
-    except Exception as e:  # pragma: no cover
-        logger.error(f"Error creating resource {data.file_path}: {e}")
-        raise HTTPException(status_code=500, detail=f"Failed to create resource: {str(e)}")
+        except HTTPException:
+            raise
+        except Exception as e:  # pragma: no cover
+            logger.error(f"Error creating resource {data.file_path}: {e}")
+            raise HTTPException(status_code=500, detail=f"Failed to create resource: {str(e)}")
 
 
 @router.put("/{entity_id}", response_model=ResourceResponse)
@@ -211,79 +258,94 @@ async def update_resource(
     Raises:
         HTTPException: 404 if entity not found, 400 for invalid paths
     """
-    try:
-        # Get existing entity by external_id
-        entity = await entity_repository.get_by_external_id(entity_id)
-        if not entity:
-            raise HTTPException(status_code=404, detail=f"Entity {entity_id} not found")
+    with telemetry.operation(
+        "api.request.resource.update",
+        entrypoint="api",
+        domain="resource",
+        action="update",
+    ):
+        try:
+            entity = await entity_repository.get_by_external_id(entity_id)
+            if not entity:
+                raise HTTPException(status_code=404, detail=f"Entity {entity_id} not found")
 
-        # Determine target file path
-        target_file_path = data.file_path if data.file_path else entity.file_path
+            target_file_path = data.file_path if data.file_path else entity.file_path
 
-        # Validate path to prevent path traversal attacks
-        project_path = PathLib(config.home)
-        if not validate_project_path(target_file_path, project_path):
-            logger.warning(
-                f"Invalid file path attempted: {target_file_path} in project {config.name}"
+            project_path = PathLib(config.home)
+            if not validate_project_path(target_file_path, project_path):
+                logger.warning(
+                    f"Invalid file path attempted: {target_file_path} in project {config.name}"
+                )
+                raise HTTPException(
+                    status_code=400,
+                    detail=f"Invalid file path: {target_file_path}. "
+                    "Path must be relative and stay within project boundaries.",
+                )
+
+            with telemetry.scope(
+                "api.resource.update.write_file",
+                domain="resource",
+                action="update",
+                phase="write_file",
+            ):
+                if data.file_path and data.file_path != entity.file_path:
+                    await file_service.ensure_directory(PathLib(target_file_path).parent)
+                    if await file_service.exists(entity.file_path):
+                        await file_service.delete_file(entity.file_path)
+                else:
+                    await file_service.ensure_directory(PathLib(target_file_path).parent)
+
+                checksum = await file_service.write_file(target_file_path, data.content)
+
+            with telemetry.scope(
+                "api.resource.update.read_metadata",
+                domain="resource",
+                action="update",
+                phase="read_metadata",
+            ):
+                file_metadata = await file_service.get_file_metadata(target_file_path)
+
+            file_name = PathLib(target_file_path).name
+            content_type = file_service.content_type(target_file_path)
+            note_type = "canvas" if target_file_path.endswith(".canvas") else "file"
+
+            with telemetry.scope(
+                "api.resource.update.update_entity",
+                domain="resource",
+                action="update",
+                phase="update_entity",
+            ):
+                updated_entity = await entity_repository.update(
+                    entity.id,
+                    {
+                        "title": file_name,
+                        "note_type": note_type,
+                        "content_type": content_type,
+                        "file_path": target_file_path,
+                        "checksum": checksum,
+                        "updated_at": file_metadata.modified_at,
+                    },
+                )
+
+            with telemetry.scope(
+                "api.resource.update.search_index",
+                domain="resource",
+                action="update",
+                phase="search_index",
+            ):
+                await search_service.index_entity(updated_entity)  # pyright: ignore
+
+            return ResourceResponse(
+                entity_id=entity.id,
+                external_id=entity.external_id,
+                file_path=target_file_path,
+                checksum=checksum,
+                size=file_metadata.size,
+                created_at=file_metadata.created_at.timestamp(),
+                modified_at=file_metadata.modified_at.timestamp(),
             )
-            raise HTTPException(
-                status_code=400,
-                detail=f"Invalid file path: {target_file_path}. "
-                "Path must be relative and stay within project boundaries.",
-            )
-
-        # If moving file, handle the move
-        if data.file_path and data.file_path != entity.file_path:
-            # Ensure new parent directory exists (no-op for S3)
-            await file_service.ensure_directory(PathLib(target_file_path).parent)
-
-            # If old file exists, remove it via file_service (for cloud compatibility)
-            if await file_service.exists(entity.file_path):
-                await file_service.delete_file(entity.file_path)
-        else:
-            # Ensure directory exists for in-place update
-            await file_service.ensure_directory(PathLib(target_file_path).parent)
-
-        # Write content to target file
-        checksum = await file_service.write_file(target_file_path, data.content)
-
-        # Get file info
-        file_metadata = await file_service.get_file_metadata(target_file_path)
-
-        # Determine file details
-        file_name = PathLib(target_file_path).name
-        content_type = file_service.content_type(target_file_path)
-        note_type = "canvas" if target_file_path.endswith(".canvas") else "file"
-
-        # Update entity using internal ID
-        updated_entity = await entity_repository.update(
-            entity.id,
-            {
-                "title": file_name,
-                "note_type": note_type,
-                "content_type": content_type,
-                "file_path": target_file_path,
-                "checksum": checksum,
-                "updated_at": file_metadata.modified_at,
-            },
-        )
-
-        # Index the updated file for search
-        await search_service.index_entity(updated_entity)  # pyright: ignore
-
-        # Return success response
-        return ResourceResponse(
-            entity_id=entity.id,
-            external_id=entity.external_id,
-            file_path=target_file_path,
-            checksum=checksum,
-            size=file_metadata.size,
-            created_at=file_metadata.created_at.timestamp(),
-            modified_at=file_metadata.modified_at.timestamp(),
-        )
-    except HTTPException:
-        # Re-raise HTTP exceptions without wrapping
-        raise
-    except Exception as e:  # pragma: no cover
-        logger.error(f"Error updating resource {entity_id}: {e}")
-        raise HTTPException(status_code=500, detail=f"Failed to update resource: {str(e)}")
+        except HTTPException:
+            raise
+        except Exception as e:  # pragma: no cover
+            logger.error(f"Error updating resource {entity_id}: {e}")
+            raise HTTPException(status_code=500, detail=f"Failed to update resource: {str(e)}")

src/basic_memory/api/v2/routers/schema_router.py

@@ -10,9 +10,15 @@ Flow: Entity loaded with eager observations/relations -> convert to tuples -> co
 
 from pathlib import Path as FilePath
 
+import frontmatter
 from fastapi import APIRouter, Path, Query
+from loguru import logger
 
-from basic_memory.deps import EntityRepositoryV2ExternalDep
+from basic_memory.deps import (
+    EntityRepositoryV2ExternalDep,
+    FileServiceV2ExternalDep,
+    LinkResolverV2ExternalDep,
+)
 from basic_memory.models.knowledge import Entity
 from basic_memory.schemas.schema import (
     ValidationReport,
@@ -67,11 +73,54 @@ def _entity_to_note_data(entity: Entity) -> NoteData:
 
 
 def _entity_frontmatter(entity: Entity) -> dict:
-    """Build a frontmatter dict from an entity for schema resolution."""
-    frontmatter = dict(entity.entity_metadata) if entity.entity_metadata else {}
+    """Build a frontmatter dict from an entity's database metadata.
+
+    Used for the notes being validated — their type and schema ref are
+    unlikely to change between syncs.
+    """
+    fm = dict(entity.entity_metadata) if entity.entity_metadata else {}
     if entity.note_type:
-        frontmatter.setdefault("type", entity.note_type)
-    return frontmatter
+        fm.setdefault("type", entity.note_type)
+    return fm
+
+
+async def _schema_frontmatter_from_file(
+    file_service: FileServiceV2ExternalDep,
+    entity: Entity,
+) -> dict:
+    """Read a schema entity's frontmatter directly from its file.
+
+    Schema definitions (field declarations, validation mode) are the source
+    of truth for validation. Reading from the file ensures schema-validate
+    always uses the latest settings, even when the file watcher hasn't
+    synced changes to entity_metadata in the database.
+    """
+    try:
+        content = await file_service.read_file_content(entity.file_path)
+        post = frontmatter.loads(content)
+        metadata = dict(post.metadata)
+
+        # Trigger: file is mid-edit and missing required schema fields
+        # Why: parse_schema_note() raises ValueError for missing entity/schema,
+        #   which would turn validation into a 500 response
+        # Outcome: fall back to last-known-good database metadata
+        if not metadata.get("entity") or not isinstance(metadata.get("schema"), dict):
+            logger.warning(
+                "Schema file has incomplete frontmatter, falling back to database metadata",
+                file_path=entity.file_path,
+            )
+            return _entity_frontmatter(entity)
+
+        return metadata
+    except Exception:
+        # Trigger: file is missing, unreadable, or has malformed frontmatter
+        # Why: fall back to database metadata rather than failing validation entirely
+        # Outcome: behaves like before this change — uses potentially stale data
+        logger.warning(
+            "Failed to read schema file, falling back to database metadata",
+            file_path=entity.file_path,
+        )
+        return _entity_frontmatter(entity)
 
 
 # --- Validation ---
@@ -80,6 +129,8 @@ def _entity_frontmatter(entity: Entity) -> dict:
 @router.post("/schema/validate", response_model=ValidationReport)
 async def validate_schema(
     entity_repository: EntityRepositoryV2ExternalDep,
+    file_service: FileServiceV2ExternalDep,
+    link_resolver: LinkResolverV2ExternalDep,
     project_id: str = Path(..., description="Project external UUID"),
     note_type: str | None = Query(None, description="Note type to validate"),
     identifier: str | None = Query(None, description="Specific note identifier"),
@@ -88,14 +139,20 @@ async def validate_schema(
 
     Validates a specific note (by identifier) or all notes of a given type.
     Returns warnings/errors based on the schema's validation mode.
+
+    Schema definitions are read directly from their files to ensure the
+    latest settings (validation mode, field declarations) are always used,
+    even when file changes haven't been synced to the database yet.
     """
     results: list[NoteValidationResponse] = []
 
     # --- Single note validation ---
     if identifier:
-        entity = await entity_repository.get_by_permalink(identifier)
+        # Resolve identifier flexibly (permalink, title, path, fuzzy)
+        # to match how read_note and other tools resolve identifiers
+        entity = await link_resolver.resolve_link(identifier)
         if not entity:
-            return ValidationReport(note_type=note_type, total_notes=0, results=[])
+            return ValidationReport(note_type=note_type, total_notes=0, total_entities=0)
 
         frontmatter = _entity_frontmatter(entity)
         schema_ref = frontmatter.get("schema")
@@ -106,12 +163,12 @@ async def validate_schema(
                 query,
                 allow_reference_match=isinstance(schema_ref, str) and query == schema_ref,
             )
-            return [_entity_frontmatter(e) for e in entities]
+            return [await _schema_frontmatter_from_file(file_service, e) for e in entities]
 
         schema_def = await resolve_schema(frontmatter, search_fn)
         if schema_def:
             result = validate_note(
-                entity.permalink or identifier,
+                entity.title or entity.permalink or identifier,
                 schema_def,
                 _entity_observations(entity),
                 _entity_relations(entity),
@@ -121,7 +178,8 @@ async def validate_schema(
 
         return ValidationReport(
             note_type=note_type or entity.note_type,
-            total_notes=1,
+            total_notes=len(results),
+            total_entities=1,
             valid_count=1 if (results and results[0].passed) else 0,
             warning_count=sum(len(r.warnings) for r in results),
             error_count=sum(len(r.errors) for r in results),
@@ -141,12 +199,12 @@ async def validate_schema(
                 query,
                 allow_reference_match=isinstance(schema_ref, str) and query == schema_ref,
             )
-            return [_entity_frontmatter(e) for e in entities]
+            return [await _schema_frontmatter_from_file(file_service, e) for e in entities]
 
         schema_def = await resolve_schema(frontmatter, search_fn)
         if schema_def:
             result = validate_note(
-                entity.permalink or entity.file_path,
+                entity.title or entity.permalink or entity.file_path,
                 schema_def,
                 _entity_observations(entity),
                 _entity_relations(entity),
@@ -215,6 +273,7 @@ async def infer_schema_endpoint(
 @router.get("/schema/diff/{note_type}", response_model=DriftReport)
 async def diff_schema_endpoint(
     entity_repository: EntityRepositoryV2ExternalDep,
+    file_service: FileServiceV2ExternalDep,
     note_type: str = Path(..., description="Note type to check for drift"),
     project_id: str = Path(..., description="Project external UUID"),
 ):
@@ -227,7 +286,7 @@ async def diff_schema_endpoint(
 
     async def search_fn(query: str) -> list[dict]:
         entities = await _find_schema_entities(entity_repository, query)
-        return [_entity_frontmatter(e) for e in entities]
+        return [await _schema_frontmatter_from_file(file_service, e) for e in entities]
 
     # Resolve schema by note type
     schema_frontmatter = {"type": note_type}

src/basic_memory/api/v2/routers/search_router.py

@@ -6,6 +6,7 @@ V1 uses string-based project names which are less efficient and less stable.
 
 from fastapi import APIRouter, HTTPException, Path
 
+from basic_memory import telemetry
 from basic_memory.api.v2.utils import to_search_results
 from basic_memory.repository.semantic_errors import (
     SemanticDependenciesMissingError,
@@ -47,29 +48,73 @@ async def search(
     Returns:
         SearchResponse with paginated search results
     """
-    offset = (page - 1) * page_size
-    # Fetch one extra item to detect whether more pages exist (N+1 trick)
-    fetch_limit = page_size + 1
-    try:
-        results = await search_service.search(query, limit=fetch_limit, offset=offset)
-    except SemanticSearchDisabledError as exc:
-        raise HTTPException(status_code=400, detail=str(exc)) from exc
-    except SemanticDependenciesMissingError as exc:
-        raise HTTPException(status_code=400, detail=str(exc)) from exc
-    except ValueError as exc:
-        raise HTTPException(status_code=400, detail=str(exc)) from exc
-
-    has_more = len(results) > page_size
-    if has_more:
-        results = results[:page_size]
-
-    search_results = await to_search_results(entity_service, results)
-    return SearchResponse(
-        results=search_results,
-        current_page=page,
+    with telemetry.operation(
+        "api.request.search",
+        entrypoint="api",
+        domain="search",
+        action="search",
+        page=page,
         page_size=page_size,
-        has_more=has_more,
-    )
+        retrieval_mode=query.retrieval_mode.value,
+        has_query=bool(
+            (query.text and query.text.strip())
+            or query.title
+            or query.permalink
+            or query.permalink_match
+        ),
+        has_filters=bool(query.note_types or query.entity_types or query.metadata_filters),
+    ):
+        offset = (page - 1) * page_size
+        fetch_limit = page_size + 1
+        try:
+            with telemetry.scope(
+                "api.search.search.execute_query",
+                domain="search",
+                action="search",
+                phase="execute_query",
+                page=page,
+                page_size=page_size,
+            ):
+                results = await search_service.search(query, limit=fetch_limit, offset=offset)
+        except SemanticSearchDisabledError as exc:
+            raise HTTPException(status_code=400, detail=str(exc)) from exc
+        except SemanticDependenciesMissingError as exc:
+            raise HTTPException(status_code=400, detail=str(exc)) from exc
+        except ValueError as exc:
+            raise HTTPException(status_code=400, detail=str(exc)) from exc
+
+        with telemetry.scope(
+            "api.search.search.paginate_results",
+            domain="search",
+            action="search",
+            phase="paginate_results",
+            result_count=len(results),
+        ):
+            has_more = len(results) > page_size
+            if has_more:
+                results = results[:page_size]
+
+        with telemetry.scope(
+            "api.search.search.hydrate_results",
+            domain="search",
+            action="search",
+            phase="hydrate_results",
+            result_count=len(results),
+        ):
+            search_results = await to_search_results(entity_service, results)
+        with telemetry.scope(
+            "api.search.search.build_response",
+            domain="search",
+            action="search",
+            phase="build_response",
+            result_count=len(search_results),
+        ):
+            return SearchResponse(
+                results=search_results,
+                current_page=page,
+                page_size=page_size,
+                has_more=has_more,
+            )
 
 
 @router.post("/search/reindex")

src/basic_memory/api/v2/utils.py

@@ -1,5 +1,7 @@
 from typing import Optional, List
 
+from basic_memory import telemetry
+from basic_memory.models import Entity as EntityModel
 from basic_memory.repository import EntityRepository
 from basic_memory.repository.search_repository import SearchIndexRow
 from basic_memory.schemas.memory import (
@@ -24,169 +26,224 @@ async def to_graph_context(
     page: Optional[int] = None,
     page_size: Optional[int] = None,
 ):
-    # First pass: collect all entity IDs needed for external_id lookup
-    # This includes: entity primary results, observation parent entities, relation from/to entities
-    entity_ids_needed: set[int] = set()
-    for context_item in context_result.results:
-        for item in (
-            [context_item.primary_result] + context_item.observations + context_item.related_results
-        ):
-            if item.type == SearchItemType.ENTITY:
-                # Entity's own ID for its external_id
-                entity_ids_needed.add(item.id)
-            elif item.type == SearchItemType.OBSERVATION:
-                # Parent entity ID for entity_external_id
-                if item.entity_id:  # pyright: ignore
-                    entity_ids_needed.add(item.entity_id)  # pyright: ignore
-            elif item.type == SearchItemType.RELATION:
-                # Source and target entity IDs for external_ids
-                if item.from_id:  # pyright: ignore
-                    entity_ids_needed.add(item.from_id)  # pyright: ignore
-                if item.to_id:
-                    entity_ids_needed.add(item.to_id)
-
-    # Batch fetch all entities at once - get both title and external_id
-    entity_title_lookup: dict[int, str] = {}
-    entity_external_id_lookup: dict[int, str] = {}
-    if entity_ids_needed:
-        entities = await entity_repository.find_by_ids(list(entity_ids_needed))
-        for e in entities:
-            entity_title_lookup[e.id] = e.title
-            entity_external_id_lookup[e.id] = e.external_id
-
-    # Helper function to convert items to summaries
-    def to_summary(item: SearchIndexRow | ContextResultRow):
-        match item.type:
-            case SearchItemType.ENTITY:
-                return EntitySummary(
-                    external_id=entity_external_id_lookup.get(item.id, ""),
-                    entity_id=item.id,
-                    title=item.title,  # pyright: ignore
-                    permalink=item.permalink,
-                    content=item.content,
-                    file_path=item.file_path,
-                    created_at=item.created_at,
-                )
-            case SearchItemType.OBSERVATION:
-                entity_ext_id = None
-                if item.entity_id:  # pyright: ignore
-                    entity_ext_id = entity_external_id_lookup.get(item.entity_id)  # pyright: ignore
-                return ObservationSummary(
-                    observation_id=item.id,
-                    entity_id=item.entity_id,  # pyright: ignore
-                    entity_external_id=entity_ext_id,
-                    title=entity_title_lookup.get(item.entity_id),  # pyright: ignore
-                    file_path=item.file_path,
-                    category=item.category,  # pyright: ignore
-                    content=item.content,  # pyright: ignore
-                    permalink=item.permalink,  # pyright: ignore
-                    created_at=item.created_at,
-                )
-            case SearchItemType.RELATION:
-                from_title = entity_title_lookup.get(item.from_id) if item.from_id else None  # pyright: ignore
-                to_title = entity_title_lookup.get(item.to_id) if item.to_id else None
-                from_ext_id = entity_external_id_lookup.get(item.from_id) if item.from_id else None  # pyright: ignore
-                to_ext_id = entity_external_id_lookup.get(item.to_id) if item.to_id else None
-                return RelationSummary(
-                    relation_id=item.id,
-                    entity_id=item.entity_id,  # pyright: ignore
-                    title=item.title,  # pyright: ignore
-                    file_path=item.file_path,
-                    permalink=item.permalink,  # pyright: ignore
-                    relation_type=item.relation_type,  # pyright: ignore
-                    from_entity=from_title,
-                    from_entity_id=item.from_id,  # pyright: ignore
-                    from_entity_external_id=from_ext_id,
-                    to_entity=to_title,
-                    to_entity_id=item.to_id,
-                    to_entity_external_id=to_ext_id,
-                    created_at=item.created_at,
-                )
-            case _:  # pragma: no cover
-                raise ValueError(f"Unexpected type: {item.type}")
-
-    # Process the hierarchical results
-    hierarchical_results = []
-    for context_item in context_result.results:
-        # Process primary result
-        primary_result = to_summary(context_item.primary_result)
-
-        # Process observations (always ObservationSummary, validated by context_service)
-        observations = [to_summary(obs) for obs in context_item.observations]
-
-        # Process related results
-        related = [to_summary(rel) for rel in context_item.related_results]
-
-        # Add to hierarchical results
-        hierarchical_results.append(
-            ContextResult(
-                primary_result=primary_result,
-                observations=observations,  # pyright: ignore[reportArgumentType]
-                related_results=related,
-            )
-        )
-
-    # Create schema metadata from service metadata
-    metadata = MemoryMetadata(
-        uri=context_result.metadata.uri,
-        types=context_result.metadata.types,
-        depth=context_result.metadata.depth,
-        timeframe=context_result.metadata.timeframe,
-        generated_at=context_result.metadata.generated_at,
-        primary_count=context_result.metadata.primary_count,
-        related_count=context_result.metadata.related_count,
-        total_results=context_result.metadata.primary_count + context_result.metadata.related_count,
-        total_relations=context_result.metadata.total_relations,
-        total_observations=context_result.metadata.total_observations,
-    )
-
-    # Return new GraphContext with just hierarchical results
-    return GraphContext(
-        results=hierarchical_results,
-        metadata=metadata,
+    with telemetry.scope(
+        "memory.hydrate_context",
+        domain="memory",
+        action="build_context",
+        phase="hydrate_context",
         page=page,
         page_size=page_size,
-        has_more=context_result.metadata.has_more,
-    )
+        result_count=len(context_result.results),
+    ):
+        # First pass: collect all entity IDs needed for external_id lookup
+        # This includes: entity primary results, observation parent entities, relation from/to entities
+        entity_ids_needed: set[int] = set()
+        for context_item in context_result.results:
+            for item in (
+                [context_item.primary_result]
+                + context_item.observations
+                + context_item.related_results
+            ):
+                if item.type == SearchItemType.ENTITY:
+                    # Entity's own ID for its external_id
+                    entity_ids_needed.add(item.id)
+                elif item.type == SearchItemType.OBSERVATION:
+                    # Parent entity ID for entity_external_id
+                    if item.entity_id:  # pyright: ignore
+                        entity_ids_needed.add(item.entity_id)  # pyright: ignore
+                elif item.type == SearchItemType.RELATION:
+                    # Source and target entity IDs for external_ids
+                    if item.from_id:  # pyright: ignore
+                        entity_ids_needed.add(item.from_id)  # pyright: ignore
+                    if item.to_id:
+                        entity_ids_needed.add(item.to_id)
+
+        # Batch fetch all entities at once - get both title and external_id
+        entity_title_lookup: dict[int, str] = {}
+        entity_external_id_lookup: dict[int, str] = {}
+        if entity_ids_needed:
+            with telemetry.scope(
+                "memory.hydrate_context.lookup_entities",
+                domain="memory",
+                action="build_context",
+                phase="lookup_entities",
+                result_count=len(entity_ids_needed),
+            ):
+                entities = await entity_repository.find_by_ids(list(entity_ids_needed))
+            for e in entities:
+                entity_title_lookup[e.id] = e.title
+                entity_external_id_lookup[e.id] = e.external_id
+
+        # Helper function to convert items to summaries
+        def to_summary(item: SearchIndexRow | ContextResultRow):
+            match item.type:
+                case SearchItemType.ENTITY:
+                    return EntitySummary(
+                        external_id=entity_external_id_lookup.get(item.id, ""),
+                        entity_id=item.id,
+                        title=item.title,  # pyright: ignore
+                        permalink=item.permalink,
+                        content=item.content,
+                        file_path=item.file_path,
+                        created_at=item.created_at,
+                    )
+                case SearchItemType.OBSERVATION:
+                    entity_ext_id = None
+                    if item.entity_id:  # pyright: ignore
+                        entity_ext_id = entity_external_id_lookup.get(item.entity_id)  # pyright: ignore
+                    return ObservationSummary(
+                        observation_id=item.id,
+                        entity_id=item.entity_id,  # pyright: ignore
+                        entity_external_id=entity_ext_id,
+                        title=entity_title_lookup.get(item.entity_id),  # pyright: ignore
+                        file_path=item.file_path,
+                        category=item.category,  # pyright: ignore
+                        content=item.content,  # pyright: ignore
+                        permalink=item.permalink,  # pyright: ignore
+                        created_at=item.created_at,
+                    )
+                case SearchItemType.RELATION:
+                    from_title = entity_title_lookup.get(item.from_id) if item.from_id else None  # pyright: ignore
+                    to_title = entity_title_lookup.get(item.to_id) if item.to_id else None
+                    from_ext_id = (
+                        entity_external_id_lookup.get(item.from_id) if item.from_id else None
+                    )  # pyright: ignore
+                    to_ext_id = entity_external_id_lookup.get(item.to_id) if item.to_id else None
+                    return RelationSummary(
+                        relation_id=item.id,
+                        entity_id=item.entity_id,  # pyright: ignore
+                        title=item.title,  # pyright: ignore
+                        file_path=item.file_path,
+                        permalink=item.permalink,  # pyright: ignore
+                        relation_type=item.relation_type,  # pyright: ignore
+                        from_entity=from_title,
+                        from_entity_id=item.from_id,  # pyright: ignore
+                        from_entity_external_id=from_ext_id,
+                        to_entity=to_title,
+                        to_entity_id=item.to_id,
+                        to_entity_external_id=to_ext_id,
+                        created_at=item.created_at,
+                    )
+                case _:  # pragma: no cover
+                    raise ValueError(f"Unexpected type: {item.type}")
+
+        with telemetry.scope(
+            "memory.hydrate_context.shape_results",
+            domain="memory",
+            action="build_context",
+            phase="shape_results",
+            result_count=len(context_result.results),
+        ):
+            hierarchical_results = []
+            for context_item in context_result.results:
+                primary_result = to_summary(context_item.primary_result)
+                observations = [to_summary(obs) for obs in context_item.observations]
+                related = [to_summary(rel) for rel in context_item.related_results]
+                hierarchical_results.append(
+                    ContextResult(
+                        primary_result=primary_result,
+                        observations=observations,  # pyright: ignore[reportArgumentType]
+                        related_results=related,
+                    )
+                )
+
+        metadata = MemoryMetadata(
+            uri=context_result.metadata.uri,
+            types=context_result.metadata.types,
+            depth=context_result.metadata.depth,
+            timeframe=context_result.metadata.timeframe,
+            generated_at=context_result.metadata.generated_at,
+            primary_count=context_result.metadata.primary_count,
+            related_count=context_result.metadata.related_count,
+            total_results=context_result.metadata.primary_count
+            + context_result.metadata.related_count,
+            total_relations=context_result.metadata.total_relations,
+            total_observations=context_result.metadata.total_observations,
+        )
+
+        return GraphContext(
+            results=hierarchical_results,
+            metadata=metadata,
+            page=page,
+            page_size=page_size,
+            has_more=context_result.metadata.has_more,
+        )
 
 
 async def to_search_results(entity_service: EntityService, results: List[SearchIndexRow]):
-    search_results = []
-    for r in results:
-        entities = await entity_service.get_entities_by_id([r.entity_id, r.from_id, r.to_id])  # pyright: ignore
+    with telemetry.scope(
+        "search.hydrate_results",
+        domain="search",
+        action="search",
+        phase="hydrate_results",
+        result_count=len(results),
+    ):
+        # Collect all unique entity IDs across all results in a single pass
+        # This avoids N+1 queries — one batch fetch instead of one per result
+        all_entity_ids: set[int] = set()
+        for result in results:
+            for eid in (result.entity_id, result.from_id, result.to_id):
+                if eid is not None:
+                    all_entity_ids.add(eid)
 
-        # Determine which IDs to set based on type
-        entity_id = None
-        observation_id = None
-        relation_id = None
+        # Single batch fetch for all entities
+        entities_by_id: dict[int, EntityModel] = {}
+        with telemetry.scope(
+            "search.hydrate_results.fetch_entities",
+            domain="search",
+            action="search",
+            phase="fetch_entities",
+            result_count=len(all_entity_ids),
+        ):
+            if all_entity_ids:
+                entities = await entity_service.get_entities_by_id(list(all_entity_ids))
+                entities_by_id = {e.id: e for e in entities}
 
-        if r.type == SearchItemType.ENTITY:
-            entity_id = r.id
-        elif r.type == SearchItemType.OBSERVATION:
-            observation_id = r.id
-            entity_id = r.entity_id  # Parent entity
-        elif r.type == SearchItemType.RELATION:
-            relation_id = r.id
-            entity_id = r.entity_id  # Parent entity
+        search_results = []
+        with telemetry.scope(
+            "search.hydrate_results.shape_results",
+            domain="search",
+            action="search",
+            phase="shape_results",
+            result_count=len(results),
+        ):
+            for result in results:
+                entity_id = None
+                observation_id = None
+                relation_id = None
 
-        search_results.append(
-            SearchResult(
-                title=r.title,  # pyright: ignore
-                type=r.type,  # pyright: ignore
-                permalink=r.permalink,
-                score=r.score,  # pyright: ignore
-                entity=entities[0].permalink if entities else None,
-                content=r.content,
-                matched_chunk=r.matched_chunk_text,
-                file_path=r.file_path,
-                metadata=r.metadata,
-                entity_id=entity_id,
-                observation_id=observation_id,
-                relation_id=relation_id,
-                category=r.category,
-                from_entity=entities[0].permalink if entities else None,
-                to_entity=entities[1].permalink if len(entities) > 1 else None,
-                relation_type=r.relation_type,
-            )
-        )
-    return search_results
+                if result.type == SearchItemType.ENTITY:
+                    entity_id = result.id
+                elif result.type == SearchItemType.OBSERVATION:
+                    observation_id = result.id
+                    entity_id = result.entity_id
+                elif result.type == SearchItemType.RELATION:
+                    relation_id = result.id
+                    entity_id = result.entity_id
+
+                # Look up entities by their specific IDs
+                parent_entity = entities_by_id.get(result.entity_id) if result.entity_id else None  # pyright: ignore
+                from_entity = entities_by_id.get(result.from_id) if result.from_id else None  # pyright: ignore
+                to_entity = entities_by_id.get(result.to_id) if result.to_id else None
+
+                search_results.append(
+                    SearchResult(
+                        title=result.title,  # pyright: ignore
+                        type=result.type,  # pyright: ignore
+                        permalink=result.permalink,
+                        score=result.score,  # pyright: ignore
+                        entity=parent_entity.permalink if parent_entity else None,
+                        content=result.content,
+                        matched_chunk=result.matched_chunk_text,
+                        file_path=result.file_path,
+                        metadata=result.metadata,
+                        entity_id=entity_id,
+                        observation_id=observation_id,
+                        relation_id=relation_id,
+                        category=result.category,
+                        from_entity=from_entity.permalink if from_entity else None,
+                        to_entity=to_entity.permalink if to_entity else None,
+                        relation_type=result.relation_type,
+                    )
+                )
+        return search_results

src/basic_memory/cli/analytics.py

@@ -25,7 +25,7 @@ import basic_memory
 # Configuration — defaults baked in, overridable via environment
 # ---------------------------------------------------------------------------
 
-_DEFAULT_UMAMI_HOST = "https://cloud.umami.is"
+_DEFAULT_UMAMI_HOST = "https://api-gateway.umami.dev"
 _DEFAULT_UMAMI_SITE_ID = "f6479898-ebaf-4e60-bce2-6dc60a3f6c5c"
 
 
@@ -76,7 +76,9 @@ def track(event_name: str, data: Optional[dict] = None) -> None:
     host = _umami_host()
     site_id = _umami_site_id()
 
+    # Umami v2 /api/send requires "type" at top level alongside "payload"
     payload = {
+        "type": "event",
         "payload": {
             "hostname": "cli.basicmemory.com",
             "language": "en",
@@ -87,7 +89,7 @@ def track(event_name: str, data: Optional[dict] = None) -> None:
                 "version": basic_memory.__version__,
                 **(data or {}),
             },
-        }
+        },
     }
 
     def _send():
@@ -97,11 +99,16 @@ def track(event_name: str, data: Optional[dict] = None) -> None:
                 data=json.dumps(payload).encode("utf-8"),
                 headers={
                     "Content-Type": "application/json",
-                    "User-Agent": f"basic-memory-cli/{basic_memory.__version__}",
+                    # Umami's bot detection rejects non-browser User-Agents
+                    "User-Agent": "Mozilla/5.0 (compatible; BasicMemoryCLI/"
+                    f"{basic_memory.__version__})",
                 },
             )
             urllib.request.urlopen(req, timeout=3)
         except Exception:
             pass  # Never break the CLI for analytics
 
-    threading.Thread(target=_send, daemon=True).start()
+    # Non-daemon so the process waits for the request to complete.
+    # The 3s urllib timeout caps the worst-case exit delay.
+    t = threading.Thread(target=_send)
+    t.start()

src/basic_memory/cli/app.py

@@ -8,9 +8,11 @@ from typing import Optional  # noqa: E402
 
 import typer  # noqa: E402
 
+from basic_memory.cli.auto_update import maybe_run_periodic_auto_update  # noqa: E402
 from basic_memory.cli.container import CliContainer, set_container  # noqa: E402
 from basic_memory.cli.promo import maybe_show_cloud_promo, maybe_show_init_line  # noqa: E402
 from basic_memory.config import init_cli_logging  # noqa: E402
+from basic_memory import telemetry  # noqa: E402
 
 
 def version_callback(value: bool) -> None:
@@ -41,6 +43,14 @@ def app_callback(
 
     # Initialize logging for CLI (file only, no stdout)
     init_cli_logging()
+    command_name = ctx.invoked_subcommand or "root"
+    ctx.with_resource(
+        telemetry.operation(
+            f"cli.command.{command_name}",
+            entrypoint="cli",
+            command_name=command_name,
+        )
+    )
 
     # --- Composition Root ---
     # Create container and read config (single point of config access)
@@ -52,10 +62,14 @@ def app_callback(
     # Outcome: one-time plain line printed before the subcommand runs.
     maybe_show_init_line(ctx.invoked_subcommand)
 
-    # Trigger: register promo as a post-command callback.
-    # Why: promo output should appear after the command's own output, not before.
-    # Outcome: promo panel renders below the command results (status tree, table, etc.).
-    ctx.call_on_close(lambda: maybe_show_cloud_promo(ctx.invoked_subcommand))
+    # Trigger: register post-command messaging callbacks.
+    # Why: informational/promo/update output belongs below command results.
+    # Outcome: command output remains primary, with optional follow-up notices afterwards.
+    def _post_command_messages() -> None:
+        maybe_show_cloud_promo(ctx.invoked_subcommand)
+        maybe_run_periodic_auto_update(ctx.invoked_subcommand)
+
+    ctx.call_on_close(_post_command_messages)
 
     # Run initialization for commands that don't use the API
     # Skip for 'mcp' command - it has its own lifespan that handles initialization
@@ -70,6 +84,7 @@ def app_callback(
         "tool",
         "reset",
         "reindex",
+        "update",
         "watch",
     }
     if (

src/basic_memory/cli/auto_update.py

@@ -0,0 +1,389 @@
+"""Automatic update checks and upgrades for the Basic Memory CLI."""
+
+from __future__ import annotations
+
+import json
+import subprocess
+import sys
+import urllib.error
+import urllib.request
+from dataclasses import dataclass
+from datetime import datetime, timedelta
+from enum import Enum
+
+from loguru import logger
+from packaging.version import InvalidVersion, Version
+from rich.console import Console
+
+import basic_memory
+from basic_memory.config import ConfigManager
+
+PACKAGE_NAME = "basic-memory"
+PYPI_JSON_URL = "https://pypi.org/pypi/basic-memory/json"
+
+PYPI_TIMEOUT_SECONDS = 5
+BREW_OUTDATED_TIMEOUT_SECONDS = 15
+UV_UPGRADE_TIMEOUT_SECONDS = 180
+BREW_UPGRADE_TIMEOUT_SECONDS = 600
+
+
+class InstallSource(str, Enum):
+    """How the running CLI appears to have been installed."""
+
+    HOMEBREW = "homebrew"
+    UV_TOOL = "uv_tool"
+    UVX = "uvx"
+    UNKNOWN = "unknown"
+
+
+class AutoUpdateStatus(str, Enum):
+    """Result classification for update checks and installs."""
+
+    SKIPPED = "skipped"
+    UP_TO_DATE = "up_to_date"
+    UPDATE_AVAILABLE = "update_available"
+    UPDATED = "updated"
+    FAILED = "failed"
+
+
+@dataclass(frozen=True)
+class AutoUpdateResult:
+    """Structured result for update checks/install attempts."""
+
+    status: AutoUpdateStatus
+    source: InstallSource
+    checked: bool
+    update_available: bool
+    updated: bool
+    latest_version: str | None = None
+    message: str | None = None
+    error: str | None = None
+    restart_recommended: bool = False
+
+
+def detect_install_source(executable: str | None = None) -> InstallSource:
+    """Infer installation source from the active interpreter path."""
+    active_executable = executable or sys.executable
+    normalized = active_executable.lower().replace("\\", "/")
+
+    if "cellar/basic-memory" in normalized:
+        return InstallSource.HOMEBREW
+    if "uv/tools/basic-memory" in normalized:
+        return InstallSource.UV_TOOL
+    if "/uv/archive-" in normalized:
+        return InstallSource.UVX
+    return InstallSource.UNKNOWN
+
+
+def _is_interactive_session() -> bool:
+    """Return whether stdin/stdout are interactive terminals."""
+    try:
+        return sys.stdin.isatty() and sys.stdout.isatty()
+    except ValueError:
+        # Trigger: stdin/stdout may be closed during transport teardown.
+        # Why: isatty() raises ValueError on closed descriptors.
+        # Outcome: treat as non-interactive and suppress periodic output.
+        return False
+
+
+def _run_subprocess(
+    command: list[str],
+    *,
+    timeout_seconds: int,
+    silent: bool,
+    capture_output: bool,
+) -> subprocess.CompletedProcess[str]:
+    """Run a subprocess with explicit stdio behavior for protocol safety."""
+    # Trigger: silent operation (MCP/background) with no need for subprocess output.
+    # Why: prevent protocol/terminal pollution from child process output.
+    # Outcome: stdout/stderr are discarded unless explicit capture is requested.
+    use_devnull = silent and not capture_output
+    stdout_target = subprocess.DEVNULL if use_devnull else subprocess.PIPE
+    stderr_target = subprocess.DEVNULL if use_devnull else subprocess.PIPE
+
+    return subprocess.run(
+        command,
+        stdin=subprocess.DEVNULL,
+        stdout=stdout_target,
+        stderr=stderr_target,
+        text=True,
+        timeout=timeout_seconds,
+        check=False,
+    )
+
+
+def _version_from_pypi() -> str:
+    """Fetch the latest published package version from PyPI."""
+    request = urllib.request.Request(
+        PYPI_JSON_URL,
+        headers={"User-Agent": f"basic-memory-cli/{basic_memory.__version__}"},
+    )
+    with urllib.request.urlopen(request, timeout=PYPI_TIMEOUT_SECONDS) as response:
+        payload = json.loads(response.read().decode("utf-8"))
+    latest = payload.get("info", {}).get("version")
+    if not latest:
+        raise RuntimeError("PyPI JSON response did not include info.version")
+    return str(latest)
+
+
+def _check_homebrew_update_available(silent: bool) -> tuple[bool, str | None]:
+    """Check whether Homebrew reports an outdated basic-memory formula."""
+    result = _run_subprocess(
+        ["brew", "outdated", "--quiet", PACKAGE_NAME],
+        timeout_seconds=BREW_OUTDATED_TIMEOUT_SECONDS,
+        silent=silent,
+        capture_output=True,
+    )
+    # Trigger: brew outdated exits 1 when the formula IS outdated (with name on stdout).
+    # Why: non-zero exit here means "outdated", not "error".
+    # Outcome: check stdout for the package name to determine outdated status.
+    stdout = (result.stdout or "").strip()
+    is_outdated = PACKAGE_NAME in stdout
+    return is_outdated, None
+
+
+def _check_pypi_update_available() -> tuple[bool, str]:
+    """Compare installed package version with PyPI latest version."""
+    latest = _version_from_pypi()
+    try:
+        current_version = Version(basic_memory.__version__)
+        latest_version = Version(latest)
+    except InvalidVersion as exc:
+        raise RuntimeError(
+            f"Could not compare versions (current={basic_memory.__version__}, latest={latest})"
+        ) from exc
+
+    return latest_version > current_version, latest
+
+
+def _manual_update_hint(source: InstallSource) -> str:
+    """Return manager-appropriate manual update instructions."""
+    if source == InstallSource.UV_TOOL:
+        return "Run `uv tool upgrade basic-memory`."
+    if source == InstallSource.HOMEBREW:
+        return "Run `brew upgrade basic-memory`."
+    return (
+        "Automatic install is not supported for this environment. "
+        "Update with your package manager (for pip: `python3 -m pip install -U basic-memory`)."
+    )
+
+
+def _save_last_checked_timestamp(config_manager: ConfigManager, checked_at: datetime) -> None:
+    """Persist the timestamp for the most recent attempted update check."""
+    config = config_manager.load_config()
+    config.auto_update_last_checked_at = checked_at
+    config_manager.save_config(config)
+
+
+def run_auto_update(
+    *,
+    force: bool = False,
+    check_only: bool = False,
+    silent: bool = False,
+    config_manager: ConfigManager | None = None,
+    now: datetime | None = None,
+    executable: str | None = None,
+) -> AutoUpdateResult:
+    """Run update check/install flow and return a structured result."""
+    manager = config_manager or ConfigManager()
+    config = manager.load_config()
+    source = detect_install_source(executable)
+    checked_at = now or datetime.now()
+
+    if source == InstallSource.UVX:
+        return AutoUpdateResult(
+            status=AutoUpdateStatus.SKIPPED,
+            source=source,
+            checked=False,
+            update_available=False,
+            updated=False,
+            message="uvx runtime detected; updates are managed by uvx cache resolution.",
+        )
+
+    if not force and not config.auto_update:
+        return AutoUpdateResult(
+            status=AutoUpdateStatus.SKIPPED,
+            source=source,
+            checked=False,
+            update_available=False,
+            updated=False,
+            message="Auto-update is disabled in config.",
+        )
+
+    if not force and config.auto_update_last_checked_at is not None:
+        try:
+            elapsed = checked_at - config.auto_update_last_checked_at
+        except TypeError:
+            # Trigger: mixed naive/aware datetimes from manual config edits.
+            # Why: datetime subtraction fails for mixed tz-awareness.
+            # Outcome: ignore the gate once and continue with a forced check path.
+            logger.warning("Auto-update interval gate skipped due to incompatible timestamp format")
+        else:
+            if elapsed < timedelta(seconds=config.update_check_interval):
+                return AutoUpdateResult(
+                    status=AutoUpdateStatus.SKIPPED,
+                    source=source,
+                    checked=False,
+                    update_available=False,
+                    updated=False,
+                    message="Update check interval has not elapsed.",
+                )
+
+    try:
+        # --- Availability check ---
+        latest_version: str | None = None
+        if source == InstallSource.HOMEBREW:
+            update_available, latest_version = _check_homebrew_update_available(silent=silent)
+        else:
+            update_available, latest_version = _check_pypi_update_available()
+
+        if not update_available:
+            return AutoUpdateResult(
+                status=AutoUpdateStatus.UP_TO_DATE,
+                source=source,
+                checked=True,
+                update_available=False,
+                updated=False,
+                latest_version=latest_version,
+                message=f"Basic Memory is up to date ({basic_memory.__version__}).",
+            )
+
+        if check_only:
+            return AutoUpdateResult(
+                status=AutoUpdateStatus.UPDATE_AVAILABLE,
+                source=source,
+                checked=True,
+                update_available=True,
+                updated=False,
+                latest_version=latest_version,
+                message=(
+                    f"Update available (latest: {latest_version or 'unknown'}). "
+                    f"{_manual_update_hint(source)}"
+                ),
+            )
+
+        if source == InstallSource.UNKNOWN:
+            return AutoUpdateResult(
+                status=AutoUpdateStatus.UPDATE_AVAILABLE,
+                source=source,
+                checked=True,
+                update_available=True,
+                updated=False,
+                latest_version=latest_version,
+                message=(
+                    f"Update available (latest: {latest_version or 'unknown'}). "
+                    f"{_manual_update_hint(source)}"
+                ),
+            )
+
+        # --- Automatic install ---
+        command = (
+            ["uv", "tool", "upgrade", PACKAGE_NAME]
+            if source == InstallSource.UV_TOOL
+            else ["brew", "upgrade", PACKAGE_NAME]
+        )
+        timeout = (
+            UV_UPGRADE_TIMEOUT_SECONDS
+            if source == InstallSource.UV_TOOL
+            else BREW_UPGRADE_TIMEOUT_SECONDS
+        )
+
+        install_result = _run_subprocess(
+            command,
+            timeout_seconds=timeout,
+            silent=silent,
+            capture_output=not silent,
+        )
+        if install_result.returncode != 0:
+            stderr = (install_result.stderr or "").strip() if install_result.stderr else ""
+            stdout = (install_result.stdout or "").strip() if install_result.stdout else ""
+            detail = stderr or stdout or "update command failed"
+            return AutoUpdateResult(
+                status=AutoUpdateStatus.FAILED,
+                source=source,
+                checked=True,
+                update_available=True,
+                updated=False,
+                latest_version=latest_version,
+                message="Automatic update failed.",
+                error=detail,
+            )
+
+        return AutoUpdateResult(
+            status=AutoUpdateStatus.UPDATED,
+            source=source,
+            checked=True,
+            update_available=True,
+            updated=True,
+            latest_version=latest_version,
+            message=(
+                "Basic Memory was updated successfully. "
+                "Restart running sessions to use the new version."
+            ),
+            restart_recommended=True,
+        )
+
+    except (
+        RuntimeError,
+        urllib.error.URLError,
+        ValueError,
+        TimeoutError,
+        subprocess.SubprocessError,
+        OSError,
+    ) as exc:
+        logger.warning(f"Auto-update check failed: {exc}")
+        return AutoUpdateResult(
+            status=AutoUpdateStatus.FAILED,
+            source=source,
+            checked=True,
+            update_available=False,
+            updated=False,
+            message="Automatic update check failed.",
+            error=str(exc),
+        )
+    finally:
+        # Trigger: we attempted a check path (including failures).
+        # Why: repeated failing checks on every command create noise and unnecessary network load.
+        # Outcome: next periodic check is gated by update_check_interval.
+        try:
+            _save_last_checked_timestamp(manager, checked_at)
+        except Exception as exc:  # pragma: no cover
+            logger.warning(f"Failed to persist auto-update timestamp: {exc}")
+
+
+def maybe_run_periodic_auto_update(
+    invoked_subcommand: str | None,
+    *,
+    config_manager: ConfigManager | None = None,
+    is_interactive: bool | None = None,
+    console: Console | None = None,
+) -> AutoUpdateResult | None:
+    """Run a periodic auto-update check for interactive CLI sessions."""
+    interactive = _is_interactive_session() if is_interactive is None else is_interactive
+    if not interactive:
+        return None
+    if invoked_subcommand in {None, "mcp", "update"}:
+        return None
+
+    result = run_auto_update(
+        force=False,
+        check_only=False,
+        silent=False,
+        config_manager=config_manager,
+    )
+
+    if result.status in {
+        AutoUpdateStatus.UPDATE_AVAILABLE,
+        AutoUpdateStatus.UPDATED,
+        AutoUpdateStatus.FAILED,
+    }:
+        out = console or Console()
+        if result.status == AutoUpdateStatus.UPDATED:
+            out.print(f"[green]{result.message}[/green]")
+        elif result.status == AutoUpdateStatus.FAILED:
+            error_detail = f" {result.error}" if result.error else ""
+            out.print(f"[yellow]{result.message}{error_detail}[/yellow]")
+        elif result.message:
+            out.print(f"[cyan]{result.message}[/cyan]")
+
+    return result

src/basic_memory/cli/commands/__init__.py

@@ -8,6 +8,7 @@ from . import (
     project,
     format,
     schema,
+    update,
 )
 
 __all__ = [
@@ -23,4 +24,5 @@ __all__ = [
     "project",
     "format",
     "schema",
+    "update",
 ]

src/basic_memory/cli/commands/cloud/api_client.py

@@ -45,14 +45,26 @@ def get_cloud_config() -> tuple[str, str, str]:
 
 async def get_authenticated_headers(auth: CLIAuth | None = None) -> dict[str, str]:
     """
-    Get authentication headers with JWT token.
-    handles jwt refresh if needed.
+    Get authentication headers for cloud API requests.
+
+    Credential priority mirrors async_client._resolve_cloud_token():
+      1. API key (config.cloud_api_key) — fast, no refresh needed
+      2. OAuth token via CLIAuth — handles JWT refresh automatically
     """
+    # --- API key (preferred) ---
+    config_manager = ConfigManager()
+    api_key = config_manager.config.cloud_api_key
+    if api_key:
+        return {"Authorization": f"Bearer {api_key}"}
+
+    # --- OAuth fallback ---
     client_id, domain, _ = get_cloud_config()
     auth_obj = auth or CLIAuth(client_id=client_id, authkit_domain=domain)
     token = await auth_obj.get_valid_token()
     if not token:
-        console.print("[red]Not authenticated. Please run 'bm cloud login' first.[/red]")
+        console.print(
+            "[red]Not authenticated. Run 'bm cloud set-key <key>' or 'bm cloud login' first.[/red]"
+        )
         raise typer.Exit(1)
 
     return {"Authorization": f"Bearer {token}"}

src/basic_memory/cli/commands/cloud/cloud_utils.py

@@ -2,10 +2,12 @@
 
 from basic_memory.cli.commands.cloud.api_client import make_api_request
 from basic_memory.config import ConfigManager
+from basic_memory.mcp.async_client import resolve_configured_workspace
 from basic_memory.schemas.cloud import (
     CloudProjectList,
     CloudProjectCreateRequest,
     CloudProjectCreateResponse,
+    ProjectVisibility,
 )
 from basic_memory.utils import generate_permalink
 
@@ -16,8 +18,25 @@ class CloudUtilsError(Exception):
     pass
 
 
+def _workspace_headers(
+    *,
+    project_name: str | None = None,
+    workspace: str | None = None,
+) -> dict[str, str]:
+    """Build optional workspace headers using the CLI config resolution chain."""
+    resolved_workspace = resolve_configured_workspace(
+        project_name=project_name,
+        workspace=workspace,
+    )
+    if resolved_workspace is None:
+        return {}
+    return {"X-Workspace-ID": resolved_workspace}
+
+
 async def fetch_cloud_projects(
     *,
+    project_name: str | None = None,
+    workspace: str | None = None,
     api_request=make_api_request,
 ) -> CloudProjectList:
     """Fetch list of projects from cloud API.
@@ -30,7 +49,11 @@ async def fetch_cloud_projects(
         config = config_manager.config
         host_url = config.cloud_host.rstrip("/")
 
-        response = await api_request(method="GET", url=f"{host_url}/proxy/v2/projects/")
+        response = await api_request(
+            method="GET",
+            url=f"{host_url}/proxy/v2/projects/",
+            headers=_workspace_headers(project_name=project_name, workspace=workspace),
+        )
 
         return CloudProjectList.model_validate(response.json())
     except Exception as e:
@@ -40,12 +63,16 @@ async def fetch_cloud_projects(
 async def create_cloud_project(
     project_name: str,
     *,
+    workspace: str | None = None,
+    visibility: ProjectVisibility = "workspace",
     api_request=make_api_request,
 ) -> CloudProjectCreateResponse:
     """Create a new project on cloud.
 
     Args:
         project_name: Name of project to create
+        workspace: Optional workspace override for tenant-scoped project creation
+        visibility: Visibility for the created cloud project
 
     Returns:
         CloudProjectCreateResponse with project details from API
@@ -62,12 +89,16 @@ async def create_cloud_project(
             name=project_name,
             path=project_path,
             set_default=False,
+            visibility=visibility,
         )
 
         response = await api_request(
             method="POST",
             url=f"{host_url}/proxy/v2/projects/",
-            headers={"Content-Type": "application/json"},
+            headers={
+                "Content-Type": "application/json",
+                **_workspace_headers(project_name=project_name, workspace=workspace),
+            },
             json_data=project_data.model_dump(),
         )
 
@@ -91,18 +122,28 @@ async def sync_project(project_name: str, force_full: bool = False) -> None:
         raise CloudUtilsError(f"Failed to sync project '{project_name}': {e}") from e
 
 
-async def project_exists(project_name: str, *, api_request=make_api_request) -> bool:
+async def project_exists(
+    project_name: str,
+    *,
+    workspace: str | None = None,
+    api_request=make_api_request,
+) -> bool:
     """Check if a project exists on cloud.
 
     Args:
         project_name: Name of project to check
+        workspace: Optional workspace override for tenant-scoped project lookup
 
     Returns:
         True if project exists, False otherwise
+
+    Raises:
+        CloudUtilsError: If the project list cannot be fetched from cloud
     """
-    try:
-        projects = await fetch_cloud_projects(api_request=api_request)
-        project_names = {p.name for p in projects.projects}
-        return project_name in project_names
-    except Exception:
-        return False
+    projects = await fetch_cloud_projects(
+        project_name=project_name,
+        workspace=workspace,
+        api_request=api_request,
+    )
+    project_names = {p.name for p in projects.projects}
+    return project_name in project_names

src/basic_memory/cli/commands/cloud/core_commands.py

@@ -85,13 +85,13 @@ def logout():
 
 @cloud_app.command("status")
 def status() -> None:
-    """Check cloud authentication state and cloud instance health."""
+    """Check cloud authentication and connection status."""
     config_manager = ConfigManager()
     config = config_manager.load_config()
     auth = CLIAuth(client_id=config.cloud_client_id, authkit_domain=config.cloud_domain)
     tokens = auth.load_tokens()
 
-    console.print("[bold blue]Cloud Authentication Status[/bold blue]")
+    console.print("[bold blue]Cloud Status[/bold blue]")
     console.print(f"  Host: {config.cloud_host}")
     console.print(
         f"  API Key: {'[green]configured[/green]' if config.cloud_api_key else '[yellow]not set[/yellow]'}"
@@ -99,17 +99,12 @@ def status() -> None:
 
     oauth_status = "[yellow]not logged in[/yellow]"
     if tokens:
-        oauth_status = (
-            "[green]token valid[/green]"
-            if auth.is_token_valid(tokens)
-            else "[yellow]token expired[/yellow]"
-        )
+        if auth.is_token_valid(tokens):
+            oauth_status = "[green]token valid[/green]"
+        else:
+            oauth_status = "[yellow]token expired[/yellow]"
     console.print(f"  OAuth: {oauth_status}")
 
-    # Get cloud configuration
-    _, _, host_url = get_cloud_config()
-    host_url = host_url.rstrip("/")
-
     has_credentials = bool(config.cloud_api_key) or tokens is not None
     if not has_credentials:
         console.print(
@@ -117,33 +112,20 @@ def status() -> None:
         )
         return
 
+    # Quick connection check — just verify we can reach the cloud
+    _, _, host_url = get_cloud_config()
+    host_url = host_url.rstrip("/")
+
     try:
-        console.print("\n[blue]Checking cloud instance health...[/blue]")
-
-        # Make API request to check health
-        response = run_with_cleanup(make_api_request(method="GET", url=f"{host_url}/proxy/health"))
-
-        health_data = response.json()
-
-        console.print("[green]Cloud instance is healthy[/green]")
-
-        # Display status details
-        if "status" in health_data:
-            console.print(f"  Status: {health_data['status']}")
-        if "version" in health_data:
-            console.print(f"  Version: {health_data['version']}")
-        if "timestamp" in health_data:
-            console.print(f"  Timestamp: {health_data['timestamp']}")
-
-        console.print("\n[dim]To sync projects, use: bm project bisync --name <project>[/dim]")
-
-    except CloudAPIError as e:
-        console.print(f"[yellow]Cloud health check failed: {e}[/yellow]")
+        run_with_cleanup(make_api_request(method="GET", url=f"{host_url}/proxy/health"))
+        console.print("\n[green]Cloud connected[/green]")
+    except CloudAPIError:
+        console.print("\n[yellow]Cloud not connected[/yellow]")
         console.print(
-            "[dim]Try re-authenticating with 'bm cloud login' or setting API key with 'bm cloud api-key save'.[/dim]"
+            "[dim]Try re-authenticating with 'bm cloud login' or 'bm cloud api-key save'.[/dim]"
         )
-    except Exception as e:
-        console.print(f"[yellow]Unexpected health check error: {e}[/yellow]")
+    except Exception:
+        console.print("\n[yellow]Cloud not connected[/yellow]")
 
 
 @cloud_app.command("setup")

src/basic_memory/cli/commands/cloud/project_sync.py

@@ -54,7 +54,7 @@ def _require_cloud_credentials(config) -> None:
 
 async def _get_cloud_project(name: str) -> ProjectItem | None:
     """Fetch a project by name from the cloud API."""
-    async with get_client() as client:
+    async with get_client(project_name=name) as client:
         projects_list = await ProjectClient(client).list_projects()
         for proj in projects_list.projects:
             if generate_permalink(proj.name) == generate_permalink(name):
@@ -129,9 +129,9 @@ def sync_project_command(
             if not dry_run:
 
                 async def _trigger_db_sync():
-                    async with get_client() as client:
+                    async with get_client(project_name=name) as client:
                         return await ProjectClient(client).sync(
-                            project_data.external_id, force_full=True
+                            project_data.external_id, force_full=False
                         )
 
                 try:
@@ -195,7 +195,10 @@ def bisync_project_command(
             # Update config — sync_entry is guaranteed non-None because
             # _get_sync_project validated local_sync_path (which comes from sync_entry)
             sync_entry = config.projects.get(name)
-            assert sync_entry is not None
+            if sync_entry is None:
+                raise RuntimeError(
+                    f"Sync entry for project '{name}' unexpectedly missing after validation"
+                )
             sync_entry.last_sync = datetime.now()
             sync_entry.bisync_initialized = True
             ConfigManager().save_config(config)
@@ -204,9 +207,9 @@ def bisync_project_command(
             if not dry_run:
 
                 async def _trigger_db_sync():
-                    async with get_client() as client:
+                    async with get_client(project_name=name) as client:
                         return await ProjectClient(client).sync(
-                            project_data.external_id, force_full=True
+                            project_data.external_id, force_full=False
                         )
 
                 try:
@@ -320,7 +323,7 @@ def setup_project_sync(
 
     async def _verify_project_exists():
         """Verify the project exists on cloud by listing all projects."""
-        async with get_client() as client:
+        async with get_client(project_name=name) as client:
             projects_list = await ProjectClient(client).list_projects()
             project_names = [p.name for p in projects_list.projects]
             if name not in project_names:

src/basic_memory/cli/commands/cloud/upload_command.py

@@ -1,5 +1,6 @@
 """Upload CLI commands for basic-memory projects."""
 
+from functools import partial
 from pathlib import Path
 
 import typer
@@ -8,12 +9,16 @@ from rich.console import Console
 from basic_memory.cli.app import cloud_app
 from basic_memory.cli.commands.command_utils import run_with_cleanup
 from basic_memory.cli.commands.cloud.cloud_utils import (
+    CloudUtilsError,
     create_cloud_project,
     project_exists,
     sync_project,
 )
 from basic_memory.cli.commands.cloud.upload import upload_path
-from basic_memory.mcp.async_client import get_cloud_control_plane_client
+from basic_memory.mcp.async_client import (
+    get_cloud_control_plane_client,
+    resolve_configured_workspace,
+)
 
 console = Console()
 
@@ -73,12 +78,20 @@ def upload(
     """
 
     async def _upload():
+        resolved_workspace = resolve_configured_workspace(project_name=project)
+
+        try:
+            project_already_exists = await project_exists(project, workspace=resolved_workspace)
+        except CloudUtilsError as e:
+            console.print(f"[red]Failed to check cloud project '{project}': {e}[/red]")
+            raise typer.Exit(1)
+
         # Check if project exists
-        if not await project_exists(project):
+        if not project_already_exists:
             if create_project:
                 console.print(f"[blue]Creating cloud project '{project}'...[/blue]")
                 try:
-                    await create_cloud_project(project)
+                    await create_cloud_project(project, workspace=resolved_workspace)
                     console.print(f"[green]Created project '{project}'[/green]")
                 except Exception as e:
                     console.print(f"[red]Failed to create project: {e}[/red]")
@@ -106,7 +119,10 @@ def upload(
             verbose=verbose,
             use_gitignore=not no_gitignore,
             dry_run=dry_run,
-            client_cm_factory=get_cloud_control_plane_client,
+            client_cm_factory=partial(
+                get_cloud_control_plane_client,
+                workspace=resolved_workspace,
+            ),
         )
         if not success:
             console.print("[red]Upload failed[/red]")
@@ -117,8 +133,10 @@ def upload(
         else:
             console.print(f"[green]Successfully uploaded to '{project}'[/green]")
 
-        # Sync project if requested (skip on dry run)
-        # Force full scan after bisync to ensure database is up-to-date with synced files
+        # Sync project if requested (skip on dry run).
+        # Trigger: upload adds new files the watcher has not observed locally.
+        # Why: force_full ensures those freshly uploaded files are indexed immediately.
+        # Outcome: upload keeps its eager reindex while sync/bisync stay incremental.
         if sync and not dry_run:
             console.print(f"[blue]Syncing project '{project}'...[/blue]")
             try:

src/basic_memory/cli/commands/db.py

@@ -11,7 +11,7 @@ from sqlalchemy.exc import OperationalError
 from basic_memory import db
 from basic_memory.cli.app import app
 from basic_memory.cli.commands.command_utils import run_with_cleanup
-from basic_memory.config import ConfigManager
+from basic_memory.config import ConfigManager, ProjectMode
 from basic_memory.repository import ProjectRepository
 from basic_memory.services.initialization import reconcile_projects_with_config
 from basic_memory.sync.sync_service import get_sync_service
@@ -169,7 +169,16 @@ async def _reindex(app_config, search: bool, embeddings: bool, project: str | No
         if project:
             projects = [p for p in projects if p.name == project]
             if not projects:
-                console.print(f"[red]Project '{project}' not found.[/red]")
+                # Check if it's a cloud-only project — those can't be reindexed locally
+                project_mode = app_config.get_project_mode(project)
+                if project_mode == ProjectMode.CLOUD:
+                    console.print(
+                        f"[yellow]Project '{project}' is a cloud project.[/yellow]\n"
+                        "Reindexing is a local operation — cloud projects are "
+                        "indexed on the server."
+                    )
+                else:
+                    console.print(f"[red]Project '{project}' not found.[/red]")
                 raise typer.Exit(1)
 
         for proj in projects:

src/basic_memory/cli/commands/doctor.py

@@ -54,6 +54,9 @@ async def run_doctor() -> None:
                 if not status.new_project:
                     raise ValueError("Failed to create doctor project")
                 project_id = status.new_project.external_id
+                # Use the resolved path from the server — when project_root is configured,
+                # the actual project directory differs from the requested temp_path
+                project_path = Path(status.new_project.path)
                 console.print(f"[green]OK[/green] Created doctor project: {project_name}")
 
                 # --- DB -> File: create an entity via API ---
@@ -68,7 +71,7 @@ async def run_doctor() -> None:
                 )
                 api_result = await knowledge_client.create_entity(api_note.model_dump(), fast=False)
 
-                api_file = temp_path / api_result.file_path
+                api_file = project_path / api_result.file_path
                 if not api_file.exists():
                     raise ValueError(f"API note file missing: {api_result.file_path}")
 
@@ -79,7 +82,7 @@ async def run_doctor() -> None:
                 console.print("[green]OK[/green] API write created file")
 
                 # --- File -> DB: write markdown file directly, then sync ---
-                parser = EntityParser(temp_path)
+                parser = EntityParser(project_path)
                 processor = MarkdownProcessor(parser)
                 manual_markdown = EntityMarkdown(
                     frontmatter=EntityFrontmatter(
@@ -93,7 +96,7 @@ async def run_doctor() -> None:
                     content=f"# {manual_note_title}\n\n- [note] File to DB check",
                 )
 
-                manual_path = temp_path / "doctor" / "manual-note.md"
+                manual_path = project_path / "doctor" / "manual-note.md"
                 await processor.write_file(manual_path, manual_markdown)
                 console.print("[green]OK[/green] Manual file written")
 

src/basic_memory/cli/commands/mcp.py

@@ -1,12 +1,14 @@
 """MCP server command with streamable HTTP transport."""
 
 import os
+import threading
 from typing import Any, Optional
 
 import typer
 from loguru import logger
 
 from basic_memory.cli.app import app
+from basic_memory.cli.auto_update import AutoUpdateStatus, run_auto_update
 from basic_memory.config import ConfigManager, init_mcp_logging
 
 
@@ -80,6 +82,22 @@ def mcp(
         os.environ["BASIC_MEMORY_MCP_PROJECT"] = project_name
         logger.info(f"MCP server constrained to project: {project_name}")
 
+    def _run_background_auto_update() -> None:
+        result = run_auto_update(force=False, check_only=False, silent=True)
+        if result.restart_recommended:
+            logger.info(
+                "A newer Basic Memory version was installed and will apply on next restart."
+            )
+        elif result.status == AutoUpdateStatus.FAILED and result.error:
+            logger.warning(f"MCP background auto-update failed: {result.error}")
+
+    # Trigger: stdio transport corresponds to local user installs.
+    # Why: server transports (HTTP/SSE) run in managed environments where
+    # package-manager self-upgrades are inappropriate.
+    # Outcome: background auto-update runs only for local stdio MCP sessions.
+    if transport == "stdio":
+        threading.Thread(target=_run_background_auto_update, daemon=True).start()
+
     # Run the MCP server (blocks)
     # Lifespan handles: initialization, migrations, file sync, cleanup
     logger.info(f"Starting MCP server with {transport.upper()} transport")

src/basic_memory/cli/commands/project.py

@@ -4,11 +4,13 @@ import json
 import os
 from datetime import datetime
 from pathlib import Path
+from typing import cast
 
 import typer
-from rich.console import Console
+from rich.console import Console, Group
 from rich.panel import Panel
 from rich.table import Table
+from rich.text import Text
 
 from basic_memory.cli.app import app
 from basic_memory.cli.auth import CLIAuth
@@ -26,6 +28,7 @@ from basic_memory.cli.commands.routing import force_routing, validate_routing_fl
 from basic_memory.config import ConfigManager, ProjectEntry, ProjectMode
 from basic_memory.mcp.async_client import get_client
 from basic_memory.mcp.clients import ProjectClient
+from basic_memory.schemas.cloud import ProjectVisibility
 from basic_memory.schemas.project_info import ProjectItem, ProjectList
 from basic_memory.utils import generate_permalink, normalize_project_path
 
@@ -44,11 +47,74 @@ def format_path(path: str) -> str:
     return path
 
 
+def make_bar(value: int, max_value: int, width: int = 40) -> Text:
+    """Create a horizontal bar chart element using Unicode blocks."""
+    if max_value == 0:
+        return Text("░" * width, style="dim")
+    filled = max(1, round(value / max_value * width)) if value > 0 else 0
+    bar = Text()
+    bar.append("█" * filled, style="cyan")
+    bar.append("░" * (width - filled), style="dim")
+    return bar
+
+
+def _normalize_project_visibility(visibility: str | None) -> ProjectVisibility:
+    """Normalize CLI visibility input to the cloud API contract."""
+    if visibility is None:
+        return "workspace"
+
+    normalized = visibility.strip().lower()
+    if normalized in {"workspace", "shared", "private"}:
+        return cast(ProjectVisibility, normalized)
+
+    raise ValueError("Invalid visibility. Expected one of: workspace, shared, private.")
+
+
+def _resolve_workspace_id(config, workspace: str | None) -> str | None:
+    """Resolve a workspace name or tenant_id to a tenant_id."""
+    from basic_memory.mcp.project_context import (
+        _workspace_choices,
+        _workspace_matches_identifier,
+        get_available_workspaces,
+    )
+
+    if workspace is not None:
+        workspaces = run_with_cleanup(get_available_workspaces())
+        matches = [ws for ws in workspaces if _workspace_matches_identifier(ws, workspace)]
+        if not matches:
+            console.print(f"[red]Error: Workspace '{workspace}' not found[/red]")
+            if workspaces:
+                console.print(f"[dim]Available:\n{_workspace_choices(workspaces)}[/dim]")
+            raise typer.Exit(1)
+        if len(matches) > 1:
+            console.print(
+                f"[red]Error: Workspace name '{workspace}' matches multiple workspaces. "
+                f"Use tenant_id instead.[/red]"
+            )
+            console.print(f"[dim]Available:\n{_workspace_choices(workspaces)}[/dim]")
+            raise typer.Exit(1)
+        return matches[0].tenant_id
+
+    if config.default_workspace:
+        return config.default_workspace
+
+    try:
+        workspaces = run_with_cleanup(get_available_workspaces())
+        if len(workspaces) == 1:
+            return workspaces[0].tenant_id
+    except Exception:
+        # Workspace resolution is optional until a command needs a specific tenant.
+        pass
+
+    return None
+
+
 @project_app.command("list")
 def list_projects(
     local: bool = typer.Option(False, "--local", help="Force local routing for this command"),
     cloud: bool = typer.Option(False, "--cloud", help="Force cloud API routing"),
     workspace: str = typer.Option(None, "--workspace", help="Cloud workspace name or tenant_id"),
+    json_output: bool = typer.Option(False, "--json", help="Output in JSON format"),
 ) -> None:
     """List Basic Memory projects from local and (when available) cloud."""
     try:
@@ -84,13 +150,9 @@ def list_projects(
 
             if _has_cloud_credentials(config):
                 try:
-                    with console.status(
-                        "[bold blue]Fetching cloud projects...", spinner="dots"
-                    ):
+                    with console.status("[bold blue]Fetching cloud projects...", spinner="dots"):
                         with force_routing(cloud=True):
-                            cloud_result = run_with_cleanup(
-                                _list_projects(effective_workspace)
-                            )
+                            cloud_result = run_with_cleanup(_list_projects(effective_workspace))
                 except Exception as exc:  # pragma: no cover
                     cloud_error = exc
 
@@ -101,9 +163,7 @@ def list_projects(
             try:
                 from basic_memory.mcp.project_context import get_available_workspaces
 
-                with console.status(
-                    "[bold blue]Resolving workspace...", spinner="dots"
-                ):
+                with console.status("[bold blue]Resolving workspace...", spinner="dots"):
                     workspaces = run_with_cleanup(get_available_workspaces())
                 matched = next(
                     (ws for ws in workspaces if ws.tenant_id == effective_workspace),
@@ -121,7 +181,7 @@ def list_projects(
         table.add_column("Cloud Path", style="green")
         table.add_column("Workspace", style="green")
         table.add_column("CLI Route", style="blue")
-        table.add_column("MCP (stdio)", style="blue")
+        table.add_column("MCP", style="blue")
         table.add_column("Sync", style="green")
         table.add_column("Default", style="magenta")
 
@@ -141,6 +201,8 @@ def list_projects(
                 project_names_by_permalink[permalink] = project.name
                 cloud_projects_by_permalink[permalink] = project
 
+        # --- Build unified project list ---
+        project_rows: list[dict] = []
         for permalink in sorted(project_names_by_permalink):
             project_name = project_names_by_permalink[permalink]
             local_project = local_projects_by_permalink.get(permalink)
@@ -155,6 +217,11 @@ def list_projects(
             elif entry and entry.mode == ProjectMode.LOCAL and entry.path:
                 local_path = format_path(normalize_project_path(entry.path))
 
+            # Clear local path for cloud-mode projects — only local projects
+            # should display a local path
+            if entry and entry.mode == ProjectMode.CLOUD:
+                local_path = ""
+
             cloud_path = ""
             if cloud_project is not None:
                 cloud_path = normalize_project_path(cloud_project.path)
@@ -170,34 +237,64 @@ def list_projects(
             else:
                 cli_route = ProjectMode.LOCAL.value
 
-            is_default = "[X]" if config.default_project == project_name else ""
+            is_default = config.default_project == project_name
 
-            has_sync = "[X]" if entry and entry.local_sync_path else ""
-            mcp_stdio_target = "local" if local_project is not None else "n/a"
+            has_sync = bool(entry and entry.local_sync_path)
+            # Determine MCP transport based on project routing mode
+            if entry and entry.mode == ProjectMode.CLOUD:
+                mcp_transport = "https"
+            elif entry is None and cloud_project is not None:
+                mcp_transport = "https"
+            else:
+                mcp_transport = "stdio"
 
             # Show workspace name (type) for cloud-sourced projects
             ws_label = ""
             if cloud_project is not None and cloud_ws_name:
                 ws_label = f"{cloud_ws_name} ({cloud_ws_type})" if cloud_ws_type else cloud_ws_name
 
-            row = [
-                project_name,
-                local_path,
-                cloud_path,
-                ws_label,
-                cli_route,
-                mcp_stdio_target,
-                has_sync,
-                is_default,
-            ]
+            row_data = {
+                "name": project_name,
+                "permalink": permalink,
+                "local_path": local_path,
+                "cloud_path": cloud_path,
+                "cli_route": cli_route,
+                "mcp_stdio": mcp_transport,
+                "sync": has_sync,
+                "is_default": is_default,
+            }
+            if ws_label:
+                row_data["workspace"] = cloud_ws_name or ""
+                if cloud_ws_type:
+                    row_data["workspace_type"] = cloud_ws_type
 
-            table.add_row(*row)
+            project_rows.append(row_data)
+
+        # --- JSON output ---
+        if json_output:
+            print(json.dumps({"projects": project_rows}, indent=2, default=str))
+            return
+
+        # --- Rich table output ---
+        for row_data in project_rows:
+            table.add_row(
+                row_data["name"],
+                row_data["local_path"],
+                row_data["cloud_path"],
+                row_data.get("workspace", "")
+                + (f" ({row_data['workspace_type']})" if row_data.get("workspace_type") else ""),
+                row_data["cli_route"],
+                row_data["mcp_stdio"],
+                "[X]" if row_data["sync"] else "",
+                "[X]" if row_data["is_default"] else "",
+            )
 
         console.print(table)
         if cloud_error is not None:
+            console.print(f"[yellow]Cloud project discovery failed: {cloud_error}[/yellow]")
             console.print(
-                "[yellow]Cloud project discovery failed. "
-                "Showing local projects only. Run 'bm cloud login' or 'bm cloud api-key save <key>'.[/yellow]"
+                "[dim]Showing local projects only. "
+                "Run 'bm cloud login' or 'bm cloud api-key save <key>' if this is a credentials issue.[/dim]"
             )
     except Exception as e:
         console.print(f"[red]Error listing projects: {str(e)}[/red]")
@@ -213,6 +310,16 @@ def add_project(
     local_path: str = typer.Option(
         None, "--local-path", help="Local sync path for cloud mode (optional)"
     ),
+    workspace: str = typer.Option(
+        None,
+        "--workspace",
+        help="Cloud workspace name or tenant_id (cloud mode only)",
+    ),
+    visibility: str = typer.Option(
+        None,
+        "--visibility",
+        help="Cloud project visibility: workspace, shared, or private",
+    ),
     set_default: bool = typer.Option(False, "--default", help="Set as default project"),
     local: bool = typer.Option(
         False, "--local", help="Force local API routing (ignore cloud mode)"
@@ -227,6 +334,8 @@ def add_project(
     Cloud mode examples:\n
         bm project add research                           # No local sync\n
         bm project add research --local-path ~/docs       # With local sync\n
+        bm project add research --cloud --visibility shared\n
+        bm project add research --cloud --workspace Personal --visibility shared\n
 
     Local mode example:\n
         bm project add research ~/Documents/research
@@ -241,6 +350,7 @@ def add_project(
 
     # Determine effective mode: default local, cloud only when explicitly requested.
     effective_cloud_mode = cloud and not local
+    resolved_workspace_id: str | None = None
 
     # Resolve local sync path early (needed for both cloud and local mode)
     local_sync_path: str | None = None
@@ -249,18 +359,31 @@ def add_project(
 
     if effective_cloud_mode:
         _require_cloud_credentials(config)
+        try:
+            resolved_visibility = _normalize_project_visibility(visibility)
+        except ValueError as e:
+            console.print(f"[red]Error: {e}[/red]")
+            raise typer.Exit(1)
+        resolved_workspace_id = _resolve_workspace_id(config, workspace)
         # Cloud mode: path auto-generated from name, local sync is optional
 
         async def _add_project():
-            async with get_client() as client:
+            async with get_client(workspace=resolved_workspace_id) as client:
                 data = {
                     "name": name,
                     "path": generate_permalink(name),
                     "local_sync_path": local_sync_path,
                     "set_default": set_default,
+                    "visibility": resolved_visibility,
                 }
                 return await ProjectClient(client).create_project(data)
     else:
+        if workspace is not None:
+            console.print("[red]Error: --workspace is only supported in cloud mode[/red]")
+            raise typer.Exit(1)
+        if visibility is not None:
+            console.print("[red]Error: --visibility is only supported in cloud mode[/red]")
+            raise typer.Exit(1)
         # Local mode: path is required
         if path is None:
             console.print("[red]Error: path argument is required in local mode[/red]")
@@ -279,25 +402,34 @@ def add_project(
             result = run_with_cleanup(_add_project())
         console.print(f"[green]{result.message}[/green]")
 
+        # Trigger: local config needs enough metadata to route future commands back to cloud.
+        # Why: explicit workspace selection and local sync state should persist across CLI sessions.
+        # Outcome: cloud-backed projects keep cloud mode, workspace_id, and optional local sync path.
+        if effective_cloud_mode and (local_sync_path or resolved_workspace_id):
+            entry = config.projects.get(name)
+            if entry:
+                entry.mode = ProjectMode.CLOUD
+                if local_sync_path:
+                    entry.path = local_sync_path
+                    entry.local_sync_path = local_sync_path
+                if resolved_workspace_id:
+                    entry.workspace_id = resolved_workspace_id
+            else:
+                # Project may not be in local config yet (cloud-only add)
+                config.projects[name] = ProjectEntry(
+                    path=local_sync_path or "",
+                    mode=ProjectMode.CLOUD,
+                    local_sync_path=local_sync_path,
+                    workspace_id=resolved_workspace_id,
+                )
+            ConfigManager().save_config(config)
+
         # Save local sync path to config if in cloud mode
         if effective_cloud_mode and local_sync_path:
             # Create local directory if it doesn't exist
             local_dir = Path(local_sync_path)
             local_dir.mkdir(parents=True, exist_ok=True)
 
-            # Update project entry — path is always the local directory
-            entry = config.projects.get(name)
-            if entry:
-                entry.path = local_sync_path
-                entry.local_sync_path = local_sync_path
-            else:
-                # Project may not be in local config yet (cloud-only add)
-                config.projects[name] = ProjectEntry(
-                    path=local_sync_path,
-                    local_sync_path=local_sync_path,
-                )
-            ConfigManager().save_config(config)
-
             console.print(f"\n[green]Local sync path configured: {local_sync_path}[/green]")
             console.print("\nNext steps:")
             console.print(f"  1. Preview: bm cloud bisync --name {name} --resync --dry-run")
@@ -531,45 +663,7 @@ def set_cloud(
         console.print("[dim]Run 'bm cloud api-key save <key>' or 'bm cloud login' first[/dim]")
         raise typer.Exit(1)
 
-    # --- Resolve workspace to tenant_id ---
-    resolved_workspace_id: str | None = None
-
-    if workspace is not None:
-        # Explicit --workspace: resolve to tenant_id via cloud lookup
-        from basic_memory.mcp.project_context import (
-            get_available_workspaces,
-            _workspace_matches_identifier,
-            _workspace_choices,
-        )
-
-        workspaces = run_with_cleanup(get_available_workspaces())
-        matches = [ws for ws in workspaces if _workspace_matches_identifier(ws, workspace)]
-        if not matches:
-            console.print(f"[red]Error: Workspace '{workspace}' not found[/red]")
-            if workspaces:
-                console.print(f"[dim]Available:\n{_workspace_choices(workspaces)}[/dim]")
-            raise typer.Exit(1)
-        if len(matches) > 1:
-            console.print(
-                f"[red]Error: Workspace name '{workspace}' matches multiple workspaces. "
-                f"Use tenant_id instead.[/red]"
-            )
-            console.print(f"[dim]Available:\n{_workspace_choices(workspaces)}[/dim]")
-            raise typer.Exit(1)
-        resolved_workspace_id = matches[0].tenant_id
-    elif config.default_workspace:
-        # Fall back to global default
-        resolved_workspace_id = config.default_workspace
-    else:
-        # Try auto-select if single workspace
-        try:
-            from basic_memory.mcp.project_context import get_available_workspaces
-
-            workspaces = run_with_cleanup(get_available_workspaces())
-            if len(workspaces) == 1:
-                resolved_workspace_id = workspaces[0].tenant_id
-        except Exception:
-            pass  # Workspace resolution is optional at set-cloud time
+    resolved_workspace_id = _resolve_workspace_id(config, workspace)
 
     config.set_project_mode(name, ProjectMode.CLOUD)
     if resolved_workspace_id:
@@ -758,99 +852,113 @@ def display_project_info(
             # Convert to JSON and print
             print(json.dumps(info.model_dump(), indent=2, default=str))
         else:
-            # Project configuration section
-            console.print(
-                Panel(
-                    f"Basic Memory version: [bold green]{info.system.version}[/bold green]\n"
-                    f"[bold]Project:[/bold] {info.project_name}\n"
-                    f"[bold]Path:[/bold] {info.project_path}\n"
-                    f"[bold]Default Project:[/bold] {info.default_project}\n",
-                    title="Basic Memory Project Info",
-                    expand=False,
-                )
-            )
+            # --- Left column: Knowledge Graph stats ---
+            left = Table.grid(padding=(0, 2))
+            left.add_column("metric", style="cyan")
+            left.add_column("value", style="green", justify="right")
 
-            # Statistics section
-            stats_table = Table(title="Statistics")
-            stats_table.add_column("Metric", style="cyan")
-            stats_table.add_column("Count", style="green")
+            left.add_row("[bold]Knowledge Graph[/bold]", "")
+            left.add_row("Entities", str(info.statistics.total_entities))
+            left.add_row("Observations", str(info.statistics.total_observations))
+            left.add_row("Relations", str(info.statistics.total_relations))
+            left.add_row("Unresolved", str(info.statistics.total_unresolved_relations))
+            left.add_row("Isolated", str(info.statistics.isolated_entities))
 
-            stats_table.add_row("Entities", str(info.statistics.total_entities))
-            stats_table.add_row("Observations", str(info.statistics.total_observations))
-            stats_table.add_row("Relations", str(info.statistics.total_relations))
-            stats_table.add_row(
-                "Unresolved Relations", str(info.statistics.total_unresolved_relations)
-            )
-            stats_table.add_row("Isolated Entities", str(info.statistics.isolated_entities))
+            # --- Right column: Embeddings ---
+            right = Table.grid(padding=(0, 2))
+            right.add_column("property", style="cyan")
+            right.add_column("value", style="green")
 
-            console.print(stats_table)
+            right.add_row("[bold]Embeddings[/bold]", "")
+            if info.embedding_status:
+                es = info.embedding_status
+                if not es.semantic_search_enabled:
+                    right.add_row("[green]●[/green] Semantic Search", "Disabled")
+                else:
+                    right.add_row("[green]●[/green] Semantic Search", "Enabled")
+                    if es.embedding_provider:
+                        right.add_row("  Provider", es.embedding_provider)
+                    if es.embedding_model:
+                        right.add_row("  Model", es.embedding_model)
+                    # Embedding coverage bar
+                    if es.total_indexed_entities > 0:
+                        coverage_bar = make_bar(
+                            es.total_entities_with_chunks,
+                            es.total_indexed_entities,
+                            width=20,
+                        )
+                        count_text = Text(
+                            f" {es.total_entities_with_chunks}/{es.total_indexed_entities}",
+                            style="green",
+                        )
+                        bar_with_count = Text.assemble("  Indexed  ", coverage_bar, count_text)
+                        right.add_row(bar_with_count, "")
+                    right.add_row("  Chunks", str(es.total_chunks))
+                    if es.reindex_recommended:
+                        right.add_row(
+                            "[yellow]●[/yellow] Status",
+                            "[yellow]Reindex recommended[/yellow]",
+                        )
+                        if es.reindex_reason:
+                            right.add_row("  Reason", f"[yellow]{es.reindex_reason}[/yellow]")
+                    else:
+                        right.add_row("[green]●[/green] Status", "[green]Up to date[/green]")
 
-            # Note types
+            # --- Compose two-column layout (content-sized, NOT Layout) ---
+            columns = Table.grid(padding=(0, 4), expand=False)
+            columns.add_row(left, right)
+
+            # --- Note Types bar chart (top 5 by count) ---
+            bars_section = None
             if info.statistics.note_types:
-                note_types_table = Table(title="Note Types")
-                note_types_table.add_column("Type", style="blue")
-                note_types_table.add_column("Count", style="green")
+                sorted_types = sorted(
+                    info.statistics.note_types.items(), key=lambda x: x[1], reverse=True
+                )
+                top_types = sorted_types[:5]
+                max_count = top_types[0][1] if top_types else 1
 
-                for note_type, count in info.statistics.note_types.items():
-                    note_types_table.add_row(note_type, str(count))
+                bars = Table.grid(padding=(0, 2), expand=False)
+                bars.add_column("type", style="cyan", width=16, justify="right")
+                bars.add_column("bar")
+                bars.add_column("count", style="green", justify="right")
 
-                console.print(note_types_table)
+                for note_type, count in top_types:
+                    bars.add_row(note_type, make_bar(count, max_count), str(count))
 
-            # Most connected entities
-            if info.statistics.most_connected_entities:  # pragma: no cover
-                connected_table = Table(title="Most Connected Entities")
-                connected_table.add_column("Title", style="blue")
-                connected_table.add_column("Permalink", style="cyan")
-                connected_table.add_column("Relations", style="green")
+                remaining = len(sorted_types) - len(top_types)
+                bars_section = Group(
+                    "[bold]Note Types[/bold]",
+                    bars,
+                    f"[dim]+{remaining} more types[/dim]" if remaining > 0 else "",
+                )
 
-                for entity in info.statistics.most_connected_entities:
-                    connected_table.add_row(
-                        entity["title"], entity["permalink"], str(entity["relation_count"])
-                    )
-
-                console.print(connected_table)
-
-            # Recent activity
-            if info.activity.recently_updated:  # pragma: no cover
-                recent_table = Table(title="Recent Activity")
-                recent_table.add_column("Title", style="blue")
-                recent_table.add_column("Type", style="cyan")
-                recent_table.add_column("Last Updated", style="green")
-
-                for entity in info.activity.recently_updated[:5]:  # Show top 5
-                    updated_at = (
-                        datetime.fromisoformat(entity["updated_at"])
-                        if isinstance(entity["updated_at"], str)
-                        else entity["updated_at"]
-                    )
-                    recent_table.add_row(
-                        entity["title"],
-                        entity["note_type"],
-                        updated_at.strftime("%Y-%m-%d %H:%M"),
-                    )
-
-                console.print(recent_table)
-
-            # Available projects
-            projects_table = Table(title="Available Projects")
-            projects_table.add_column("Name", style="blue")
-            projects_table.add_column("Path", style="cyan")
-            projects_table.add_column("Default", style="green")
-
-            for name, proj_info in info.available_projects.items():
-                is_default = name == info.default_project
-                project_path = proj_info["path"]
-                projects_table.add_row(name, project_path, "[X]" if is_default else "")
-
-            console.print(projects_table)
-
-            # Timestamp
+            # --- Footer ---
             current_time = (
                 datetime.fromisoformat(str(info.system.timestamp))
                 if isinstance(info.system.timestamp, str)
                 else info.system.timestamp
             )
-            console.print(f"\nTimestamp: [cyan]{current_time.strftime('%Y-%m-%d %H:%M:%S')}[/cyan]")
+            footer = (
+                f"[dim]{format_path(info.project_path)}  "
+                f"default: {info.default_project}  "
+                f"{current_time.strftime('%Y-%m-%d %H:%M')}[/dim]"
+            )
+
+            # --- Assemble dashboard ---
+            parts: list = [columns, ""]
+            if bars_section:
+                parts.extend([bars_section, ""])
+            parts.append(footer)
+            body = Group(*parts)
+
+            console.print(
+                Panel(
+                    body,
+                    title=f"[bold]{info.project_name}[/bold]",
+                    subtitle=f"Basic Memory {info.system.version}",
+                    expand=False,
+                )
+            )
 
     except typer.Exit:
         raise

src/basic_memory/cli/commands/schema.py

@@ -173,6 +173,7 @@ def validate(
         typer.Option(help="The project name."),
     ] = None,
     strict: bool = typer.Option(False, "--strict", help="Exit with error on validation failures"),
+    json_output: bool = typer.Option(False, "--json", help="Output in JSON format"),
     local: bool = typer.Option(
         False, "--local", help="Force local API routing (ignore cloud mode)"
     ),
@@ -183,6 +184,7 @@ def validate(
     TARGET can be a note path (e.g., people/ada-lovelace.md) or a note type
     (e.g., person). If omitted, validates all notes that have schemas.
 
+    Use --json for machine-readable output.
     Use --strict to exit with error code 1 if any validation errors are found.
     Use --local to force local routing when cloud mode is enabled.
     Use --cloud to force cloud routing when cloud mode is disabled.
@@ -211,12 +213,19 @@ def validate(
 
         # Handle error responses
         if isinstance(result, dict) and "error" in result:
-            console.print(f"[yellow]{result['error']}[/yellow]")
+            if json_output:
+                print(json.dumps(result, indent=2, default=str))
+            else:
+                console.print(f"[yellow]{result['error']}[/yellow]")
             return
 
         # output_format="json" guarantees a dict return
         assert isinstance(result, dict)
-        _render_validate_table(result)
+
+        if json_output:
+            print(json.dumps(result, indent=2, default=str))
+        else:
+            _render_validate_table(result)
 
         if strict and result.get("error_count", 0) > 0:
             raise typer.Exit(1)
@@ -245,6 +254,7 @@ def infer(
         0.25, "--threshold", help="Minimum frequency for optional fields (0-1)"
     ),
     save: bool = typer.Option(False, "--save", help="Save inferred schema to schema/ directory"),
+    json_output: bool = typer.Option(False, "--json", help="Output in JSON format"),
     local: bool = typer.Option(
         False, "--local", help="Force local API routing (ignore cloud mode)"
     ),
@@ -258,6 +268,7 @@ def infer(
     Fields present in 95%+ of notes become required. Fields above the
     threshold (default 25%) become optional. Fields below threshold are excluded.
 
+    Use --json for machine-readable output.
     Use --local to force local routing when cloud mode is enabled.
     Use --cloud to force cloud routing when cloud mode is disabled.
     """
@@ -277,7 +288,10 @@ def infer(
 
         # Handle error responses
         if isinstance(result, dict) and "error" in result:
-            console.print(f"[yellow]{result['error']}[/yellow]")
+            if json_output:
+                print(json.dumps(result, indent=2, default=str))
+            else:
+                console.print(f"[yellow]{result['error']}[/yellow]")
             return
 
         # output_format="json" guarantees a dict return
@@ -285,10 +299,16 @@ def infer(
 
         # Handle zero notes
         if result.get("notes_analyzed", 0) == 0:
-            console.print(f"[yellow]No notes found with type: {note_type}[/yellow]")
+            if json_output:
+                print(json.dumps(result, indent=2, default=str))
+            else:
+                console.print(f"[yellow]No notes found with type: {note_type}[/yellow]")
             return
 
-        _render_infer_table(result)
+        if json_output:
+            print(json.dumps(result, indent=2, default=str))
+        else:
+            _render_infer_table(result)
 
         if save:
             console.print(
@@ -316,6 +336,7 @@ def diff(
         Optional[str],
         typer.Option(help="The project name."),
     ] = None,
+    json_output: bool = typer.Option(False, "--json", help="Output in JSON format"),
     local: bool = typer.Option(
         False, "--local", help="Force local API routing (ignore cloud mode)"
     ),
@@ -327,6 +348,7 @@ def diff(
     are actually structured. Identifies new fields,
     dropped fields, and cardinality changes.
 
+    Use --json for machine-readable output.
     Use --local to force local routing when cloud mode is enabled.
     Use --cloud to force cloud routing when cloud mode is disabled.
     """
@@ -345,12 +367,19 @@ def diff(
 
         # Handle error responses
         if isinstance(result, dict) and "error" in result:
-            console.print(f"[yellow]{result['error']}[/yellow]")
+            if json_output:
+                print(json.dumps(result, indent=2, default=str))
+            else:
+                console.print(f"[yellow]{result['error']}[/yellow]")
             return
 
         # output_format="json" guarantees a dict return
         assert isinstance(result, dict)
-        _render_diff_output(result)
+
+        if json_output:
+            print(json.dumps(result, indent=2, default=str))
+        else:
+            _render_diff_output(result)
     except ValueError as e:
         console.print(f"[red]Error: {e}[/red]")
         raise typer.Exit(1)

src/basic_memory/cli/commands/status.py

@@ -1,5 +1,6 @@
 """Status command for basic-memory CLI."""
 
+import json
 from typing import Set, Dict
 from typing import Annotated, Optional
 
@@ -141,21 +142,20 @@ def display_changes(
     console.print(Panel(tree, expand=False))
 
 
-async def run_status(project: Optional[str] = None, verbose: bool = False):  # pragma: no cover
-    """Check sync status of files vs database."""
+async def run_status(
+    project: Optional[str] = None,
+) -> tuple[str, SyncReportResponse]:
+    """Fetch sync status of files vs database.
+
+    Returns (project_name, sync_report) for the caller to render.
+    """
     # Resolve default project so get_client() can route per-project
     project = project or ConfigManager().default_project
 
-    try:
-        async with get_client(project_name=project) as client:
-            project_item = await get_active_project(client, project, None)
-            sync_report = await ProjectClient(client).get_status(project_item.external_id)
-
-            display_changes(project_item.name, "Status", sync_report, verbose)
-
-    except (ValueError, ToolError) as e:
-        console.print(f"[red]Error: {e}[/red]")
-        raise typer.Exit(1)
+    async with get_client(project_name=project) as client:
+        project_item = await get_active_project(client, project, None)
+        sync_report = await ProjectClient(client).get_status(project_item.external_id)
+        return project_item.name, sync_report
 
 
 @app.command()
@@ -165,6 +165,7 @@ def status(
         typer.Option(help="The project name."),
     ] = None,
     verbose: bool = typer.Option(False, "--verbose", "-v", help="Show detailed file information"),
+    json_output: bool = typer.Option(False, "--json", help="Output in JSON format"),
     local: bool = typer.Option(
         False, "--local", help="Force local API routing (ignore cloud mode)"
     ),
@@ -172,6 +173,7 @@ def status(
 ):
     """Show sync status between files and database.
 
+    Use --json for machine-readable output.
     Use --local to force local routing when cloud mode is enabled.
     Use --cloud to force cloud routing when cloud mode is disabled.
     """
@@ -187,11 +189,24 @@ def status(
         if not local and not cloud:
             local = True
         with force_routing(local=local, cloud=cloud):
-            run_with_cleanup(run_status(project, verbose))  # pragma: no cover
-    except ValueError as e:
-        console.print(f"[red]Error: {e}[/red]")
+            project_name, sync_report = run_with_cleanup(run_status(project))
+
+        if json_output:
+            print(json.dumps(sync_report.model_dump(mode="json"), indent=2, default=str))
+        else:
+            display_changes(project_name, "Status", sync_report, verbose)
+    except (ValueError, ToolError) as e:
+        if json_output:
+            print(json.dumps({"error": str(e)}, indent=2))
+        else:
+            console.print(f"[red]Error: {e}[/red]")
         raise typer.Exit(code=1)
+    except typer.Exit:
+        raise
     except Exception as e:
         logger.error(f"Error checking status: {e}")
-        typer.echo(f"Error checking status: {e}", err=True)
+        if json_output:
+            print(json.dumps({"error": str(e)}, indent=2))
+        else:
+            typer.echo(f"Error checking status: {e}", err=True)
         raise typer.Exit(code=1)  # pragma: no cover

src/basic_memory/cli/commands/tool.py

@@ -485,7 +485,7 @@ def search_notes(
         with force_routing(local=local, cloud=cloud):
             result = run_with_cleanup(
                 mcp_search(
-                    query=query or "",
+                    query=query or None,
                     project=project,
                     workspace=workspace,
                     search_type=search_type,

src/basic_memory/cli/commands/update.py

@@ -0,0 +1,40 @@
+"""Manual update command for Basic Memory CLI."""
+
+import typer
+from rich.console import Console
+
+from basic_memory.cli.app import app
+from basic_memory.cli.auto_update import AutoUpdateStatus, run_auto_update
+
+console = Console()
+
+
+@app.command("update")
+def update(
+    check: bool = typer.Option(
+        False,
+        "--check",
+        help="Check for updates only (do not install).",
+    ),
+) -> None:
+    """Check for updates and install when supported."""
+    result = run_auto_update(force=True, check_only=check, silent=False)
+
+    if result.status == AutoUpdateStatus.FAILED:
+        detail = f" {result.error}" if result.error else ""
+        console.print(f"[red]{result.message or 'Update failed.'}{detail}[/red]")
+        raise typer.Exit(1)
+
+    if result.status == AutoUpdateStatus.UPDATED:
+        console.print(f"[green]{result.message or 'Basic Memory updated successfully.'}[/green]")
+        return
+
+    if result.status == AutoUpdateStatus.UP_TO_DATE:
+        console.print(f"[green]{result.message or 'Basic Memory is up to date.'}[/green]")
+        return
+
+    if result.status == AutoUpdateStatus.UPDATE_AVAILABLE:
+        console.print(f"[cyan]{result.message or 'Update available.'}[/cyan]")
+        return
+
+    console.print(f"[dim]{result.message or 'No update action was performed.'}[/dim]")

src/basic_memory/cli/main.py

@@ -28,6 +28,7 @@ if not _version_only_invocation(sys.argv[1:]):
         schema,
         status,
         tool,
+        update,
     )
 
 warnings.filterwarnings("ignore")  # pragma: no cover

src/basic_memory/cli/promo.py

@@ -12,7 +12,7 @@ from basic_memory.config import ConfigManager
 
 OSS_DISCOUNT_CODE = "BMFOSS"
 CLOUD_LEARN_MORE_URL = (
-    "https://basicmemory.com?utm_source=bm-cli&utm_medium=promo&utm_campaign=cloud-upsell"
+    "https://basicmemory.com?utm_source=bm-foss&utm_medium=promo&utm_campaign=cloud-upsell"
 )
 
 
@@ -24,7 +24,13 @@ def _promos_disabled_by_env() -> bool:
 
 def _is_interactive_session() -> bool:
     """Return whether stdin/stdout are interactive terminals."""
-    return sys.stdin.isatty() and sys.stdout.isatty()
+    try:
+        return sys.stdin.isatty() and sys.stdout.isatty()
+    except ValueError:
+        # Trigger: stdin/stdout already closed (e.g., MCP stdio transport shutdown)
+        # Why: isatty() raises ValueError on closed file descriptors
+        # Outcome: treat as non-interactive, suppressing promo output
+        return False
 
 
 def _build_cloud_promo_message() -> str:

src/basic_memory/config.py

@@ -3,16 +3,19 @@
 import importlib.util
 import json
 import os
+import shutil
 from dataclasses import dataclass
 from datetime import datetime
+from enum import Enum
 from pathlib import Path
 from typing import Any, Dict, Literal, Optional, List, Tuple
-from enum import Enum
 
 from loguru import logger
 from pydantic import AliasChoices, BaseModel, Field, model_validator
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
+from basic_memory import __version__
+from basic_memory.telemetry import configure_telemetry
 from basic_memory.utils import setup_logging, generate_permalink
 
 
@@ -139,6 +142,24 @@ class BasicMemoryConfig(BaseSettings):
     # overridden by ~/.basic-memory/config.json
     log_level: str = "INFO"
 
+    # Optional Logfire telemetry (disabled by default)
+    logfire_enabled: bool = Field(
+        default=False,
+        description="Enable Logfire instrumentation for local development or managed deployments.",
+    )
+    logfire_send_to_logfire: bool = Field(
+        default=False,
+        description="When true, allow Logfire to export telemetry to the configured backend.",
+    )
+    logfire_service_name: str = Field(
+        default="basic-memory",
+        description="Base service name used when constructing entrypoint-specific Logfire service names.",
+    )
+    logfire_environment: str | None = Field(
+        default=None,
+        description="Optional override for Logfire environment. Defaults to env when unset.",
+    )
+
     # Database configuration
     database_backend: DatabaseBackend = Field(
         default=DatabaseBackend.SQLITE,
@@ -172,6 +193,25 @@ class BasicMemoryConfig(BaseSettings):
         description="Batch size for embedding generation.",
         gt=0,
     )
+    semantic_embedding_sync_batch_size: int = Field(
+        default=64,
+        description="Batch size for vector sync orchestration flushes.",
+        gt=0,
+    )
+    semantic_embedding_cache_dir: str | None = Field(
+        default=None,
+        description="Optional cache directory for FastEmbed model artifacts.",
+    )
+    semantic_embedding_threads: int | None = Field(
+        default=None,
+        description="Optional FastEmbed runtime thread count override.",
+        gt=0,
+    )
+    semantic_embedding_parallel: int | None = Field(
+        default=None,
+        description="Optional FastEmbed embed() parallelism override.",
+        gt=0,
+    )
     semantic_vector_k: int = Field(
         default=100,
         description="Vector candidate count for vector and hybrid retrieval.",
@@ -183,6 +223,12 @@ class BasicMemoryConfig(BaseSettings):
         ge=0.0,
         le=1.0,
     )
+    default_search_type: Literal["text", "vector", "hybrid"] | None = Field(
+        default=None,
+        description="Default search type for search_notes when not specified per-query. "
+        "Valid values: text, vector, hybrid. "
+        "When unset, defaults to 'hybrid' if semantic search is enabled, otherwise 'text'.",
+    )
 
     # Database connection pool configuration (Postgres only)
     db_pool_size: int = Field(
@@ -245,6 +291,16 @@ class BasicMemoryConfig(BaseSettings):
         description="Disable automatic permalink generation in frontmatter. When enabled, new notes won't have permalinks added and sync won't update permalinks. Existing permalinks will still work for reading.",
     )
 
+    write_note_overwrite_default: bool = Field(
+        default=False,
+        description=(
+            "Default value for write_note's overwrite parameter. "
+            "When False (default), write_note errors if note already exists. "
+            "Set to True to restore pre-v0.20 upsert behavior. "
+            "Env: BASIC_MEMORY_WRITE_NOTE_OVERWRITE_DEFAULT"
+        ),
+    )
+
     ensure_frontmatter_on_sync: bool = Field(
         default=True,
         description="Ensure markdown files have frontmatter during sync by adding derived title/type/permalink when missing. When combined with disable_permalinks=True, this setting takes precedence for missing-frontmatter files and still writes permalinks.",
@@ -321,6 +377,22 @@ class BasicMemoryConfig(BaseSettings):
         description="Most recent cloud promo version shown in CLI.",
     )
 
+    auto_update: bool = Field(
+        default=True,
+        description="Enable automatic CLI update checks and installs when supported.",
+    )
+
+    update_check_interval: int = Field(
+        default=86400,
+        description="Seconds between automatic update checks.",
+        gt=0,
+    )
+
+    auto_update_last_checked_at: Optional[datetime] = Field(
+        default=None,
+        description="Timestamp of the last attempted automatic update check.",
+    )
+
     cloud_api_key: Optional[str] = Field(
         default=None,
         description="API key for cloud access (bmc_ prefixed). Account-level, not per-project.",
@@ -599,6 +671,12 @@ class BasicMemoryConfig(BaseSettings):
 
 # Module-level cache for configuration
 _CONFIG_CACHE: Optional[BasicMemoryConfig] = None
+# Track config file mtime+size so cross-process changes (e.g. `bm project set-cloud`
+# in a separate terminal) invalidate the cache in long-lived processes like the
+# MCP stdio server. Using both mtime and size guards against coarse-granularity
+# filesystems where two writes within the same second share the same mtime.
+_CONFIG_MTIME: Optional[float] = None
+_CONFIG_SIZE: Optional[int] = None
 
 
 class ConfigManager:
@@ -632,13 +710,38 @@ class ConfigManager:
         Environment variables take precedence over file config values,
         following Pydantic Settings best practices.
 
-        Uses module-level cache for performance across ConfigManager instances.
+        Uses module-level cache with file mtime validation so that
+        cross-process config changes (e.g. `bm project set-cloud` in a
+        separate terminal) are picked up by long-lived processes like
+        the MCP stdio server.
         """
-        global _CONFIG_CACHE
+        global _CONFIG_CACHE, _CONFIG_MTIME, _CONFIG_SIZE
 
-        # Return cached config if available
+        # Trigger: cached config exists but the on-disk file may have been
+        # modified by another process (CLI command in a different terminal).
+        # Why: the MCP server is long-lived; without this check it would
+        # serve stale project routing forever.
+        # Outcome: cheap os.stat() per access; re-read only when mtime or size differs.
         if _CONFIG_CACHE is not None:
-            return _CONFIG_CACHE
+            try:
+                st = self.config_file.stat()
+                current_mtime = st.st_mtime
+                current_size = st.st_size
+            except OSError:
+                current_mtime = None
+                current_size = None
+
+            if (
+                current_mtime is not None
+                and current_mtime == _CONFIG_MTIME
+                and current_size == _CONFIG_SIZE
+            ):
+                return _CONFIG_CACHE
+
+            # mtime/size changed or file gone — invalidate and fall through to re-read
+            _CONFIG_CACHE = None
+            _CONFIG_MTIME = None
+            _CONFIG_SIZE = None
 
         if self.config_file.exists():
             try:
@@ -693,9 +796,21 @@ class ConfigManager:
 
                 _CONFIG_CACHE = BasicMemoryConfig(**merged_data)
 
+                # Record mtime+size so subsequent calls detect cross-process changes
+                try:
+                    st = self.config_file.stat()
+                    _CONFIG_MTIME = st.st_mtime
+                    _CONFIG_SIZE = st.st_size
+                except OSError:
+                    _CONFIG_MTIME = None
+                    _CONFIG_SIZE = None
+
                 # Re-save to normalize legacy config into current format
                 if needs_resave:
-                    logger.info("Migrating config to current format")
+                    # Create backup before overwriting so users can revert if needed
+                    backup_path = self.config_file.with_suffix(".json.bak")
+                    shutil.copy2(self.config_file, backup_path)
+                    logger.info(f"Migrating config to current format (backup: {backup_path})")
                     save_basic_memory_config(self.config_file, _CONFIG_CACHE)
 
                 return _CONFIG_CACHE
@@ -720,10 +835,12 @@ class ConfigManager:
 
     def save_config(self, config: BasicMemoryConfig) -> None:
         """Save configuration to file and invalidate cache."""
-        global _CONFIG_CACHE
+        global _CONFIG_CACHE, _CONFIG_MTIME, _CONFIG_SIZE
         save_basic_memory_config(self.config_file, config)
         # Invalidate cache so next load_config() reads fresh data
         _CONFIG_CACHE = None
+        _CONFIG_MTIME = None
+        _CONFIG_SIZE = None
 
     @property
     def projects(self) -> Dict[str, str]:
@@ -858,33 +975,50 @@ def save_basic_memory_config(file_path: Path, config: BasicMemoryConfig) -> None
 # Logging initialization functions for different entry points
 
 
-def init_cli_logging() -> None:  # pragma: no cover
+def _configure_logfire_for_entrypoint(entrypoint: str) -> None:
+    """Configure optional Logfire telemetry for a specific entrypoint."""
+    config = ConfigManager().config
+    service_name = f"{config.logfire_service_name}-{entrypoint}"
+    environment = config.logfire_environment or config.env
+    configure_telemetry(
+        service_name=service_name,
+        environment=environment,
+        service_version=__version__,
+        enable_logfire=config.logfire_enabled,
+        send_to_logfire=config.logfire_send_to_logfire,
+    )
+
+
+def init_cli_logging() -> None:
     """Initialize logging for CLI commands - file only.
 
     CLI commands should not log to stdout to avoid interfering with
     command output and shell integration.
     """
     log_level = os.getenv("BASIC_MEMORY_LOG_LEVEL", "INFO")
+    _configure_logfire_for_entrypoint("cli")
     setup_logging(log_level=log_level, log_to_file=True)
 
 
-def init_mcp_logging() -> None:  # pragma: no cover
+def init_mcp_logging() -> None:
     """Initialize logging for MCP server - file only.
 
     MCP server must not log to stdout as it would corrupt the
     JSON-RPC protocol communication.
     """
     log_level = os.getenv("BASIC_MEMORY_LOG_LEVEL", "INFO")
+    _configure_logfire_for_entrypoint("mcp")
     setup_logging(log_level=log_level, log_to_file=True)
 
 
-def init_api_logging() -> None:  # pragma: no cover
+def init_api_logging() -> None:
     """Initialize logging for API server.
 
     Cloud mode (BASIC_MEMORY_CLOUD_MODE=1): stdout with structured context
     Local mode: file only
     """
     log_level = os.getenv("BASIC_MEMORY_LOG_LEVEL", "INFO")
+    _configure_logfire_for_entrypoint("api")
     cloud_mode = os.getenv("BASIC_MEMORY_CLOUD_MODE", "").lower() in ("1", "true")
     if cloud_mode:
         setup_logging(log_level=log_level, log_to_stdout=True, structured_context=True)

src/basic_memory/db.py

@@ -43,40 +43,37 @@ if sys.platform == "win32":  # pragma: no cover
 _engine: Optional[AsyncEngine] = None
 _session_maker: Optional[async_sessionmaker[AsyncSession]] = None
 
-# Alembic revision that enables one-time automatic embedding backfill.
-SEMANTIC_EMBEDDING_BACKFILL_REVISION = "i2c3d4e5f6g7"
 
-
-async def _load_applied_alembic_revisions(
+async def _needs_semantic_embedding_backfill(
+    app_config: BasicMemoryConfig,
     session_maker: async_sessionmaker[AsyncSession],
-) -> set[str]:
-    """Load applied Alembic revisions from alembic_version.
+) -> bool:
+    """Check if entities exist but vector embeddings are empty.
 
-    Returns an empty set when the version table does not exist yet
-    (fresh database before first migration).
+    This is the reliable way to detect that embeddings need to be generated,
+    regardless of how migrations were applied (fresh DB, upgrade, reset, etc.).
     """
+    if not app_config.semantic_search_enabled:
+        return False
+
     try:
         async with scoped_session(session_maker) as session:
-            result = await session.execute(text("SELECT version_num FROM alembic_version"))
-            return {str(row[0]) for row in result.fetchall() if row[0]}
+            entity_count = (
+                await session.execute(text("SELECT COUNT(*) FROM entity"))
+            ).scalar() or 0
+            if entity_count == 0:
+                return False
+
+            # Check if vector chunks table exists and is empty
+            embedding_count = (
+                await session.execute(text("SELECT COUNT(*) FROM search_vector_chunks"))
+            ).scalar() or 0
+
+            return embedding_count == 0
     except Exception as exc:
-        error_message = str(exc).lower()
-        if "alembic_version" in error_message and (
-            "no such table" in error_message or "does not exist" in error_message
-        ):
-            return set()
-        raise
-
-
-def _should_run_semantic_embedding_backfill(
-    revisions_before_upgrade: set[str],
-    revisions_after_upgrade: set[str],
-) -> bool:
-    """Check if this migration run newly applied the backfill-trigger revision."""
-    return (
-        SEMANTIC_EMBEDDING_BACKFILL_REVISION in revisions_after_upgrade
-        and SEMANTIC_EMBEDDING_BACKFILL_REVISION not in revisions_before_upgrade
-    )
+        # Table might not exist yet (pre-migration)
+        logger.debug(f"Could not check embedding status: {exc}")
+        return False
 
 
 async def _run_semantic_embedding_backfill(
@@ -128,8 +125,13 @@ async def _run_semantic_embedding_backfill(
             project_id=project_id,
             app_config=app_config,
         )
-        for entity_id in entity_ids:
-            await search_repository.sync_entity_vectors(entity_id)
+        batch_result = await search_repository.sync_entity_vectors_batch(entity_ids)
+        if batch_result.entities_failed > 0:
+            logger.warning(
+                "Automatic semantic embedding backfill encountered entity failures: "
+                f"project={project_name}, failed={batch_result.entities_failed}, "
+                f"failed_entity_ids={batch_result.failed_entity_ids}"
+            )
 
     logger.info(
         "Automatic semantic embedding backfill complete: "
@@ -478,23 +480,6 @@ async def run_migrations(
     logger.info("Running database migrations...")
     temp_engine: AsyncEngine | None = None
     try:
-        revisions_before_upgrade: set[str] = set()
-        # Trigger: run_migrations() can be invoked before module-level session maker is set.
-        # Why: we still need reliable before/after revision detection for one-time backfill.
-        # Outcome: create a short-lived session maker when needed, then dispose it immediately.
-        if _session_maker is None:
-            precheck_engine, temp_session_maker = _create_engine_and_session(
-                app_config.database_path,
-                database_type,
-                app_config,
-            )
-            try:
-                revisions_before_upgrade = await _load_applied_alembic_revisions(temp_session_maker)
-            finally:
-                await precheck_engine.dispose()
-        else:
-            revisions_before_upgrade = await _load_applied_alembic_revisions(_session_maker)
-
         # Get the absolute path to the alembic directory relative to this file
         alembic_dir = Path(__file__).parent / "alembic"
         config = Config()
@@ -536,12 +521,14 @@ async def run_migrations(
         else:
             await SQLiteSearchRepository(session_maker, 1).init_search_index()
 
-        revisions_after_upgrade = await _load_applied_alembic_revisions(session_maker)
-        if _should_run_semantic_embedding_backfill(
-            revisions_before_upgrade,
-            revisions_after_upgrade,
-        ):
-            await _run_semantic_embedding_backfill(app_config, session_maker)
+        # Check if backfill is needed — actual backfill runs in background
+        # from the MCP server lifespan to avoid blocking startup.
+        if await _needs_semantic_embedding_backfill(app_config, session_maker):
+            logger.info(
+                "Semantic embeddings missing — backfill will run in background after startup"
+            )
+        else:
+            logger.info("Semantic embeddings: up to date")
     except Exception as e:  # pragma: no cover
         logger.error(f"Error running migrations: {e}")
         raise

src/basic_memory/file_utils.py

@@ -447,6 +447,11 @@ def sanitize_for_filename(text: str, replacement: str = "-") -> str:
     # compress multiple, repeated replacements
     text = re.sub(f"{re.escape(replacement)}+", replacement, text)
 
+    # Strip trailing periods — they cause "hi-everyone..md" double-dot filenames
+    # when ".md" is appended, which triggers path traversal false positives.
+    # Trailing periods are also invalid on Windows filesystems.
+    text = text.strip(".")
+
     return text.strip(replacement)
 
 

src/basic_memory/markdown/entity_parser.py

@@ -88,6 +88,22 @@ def normalize_frontmatter_value(value: Any) -> Any:
     return value
 
 
+def _coerce_to_string(value: Any) -> str:
+    """Coerce a frontmatter value to a string.
+
+    YAML can parse scalar-looking fields as lists when the author uses block
+    sequence syntax.  For fields like ``title`` and ``type`` that *must* be
+    strings, this helper converts lists to a comma-separated string and any
+    other non-string type via ``str()``.
+    """
+    if isinstance(value, str):
+        return value
+    if isinstance(value, list):
+        # Join list items, converting each to string first
+        return ", ".join(str(item) for item in value)
+    return str(value)
+
+
 def normalize_frontmatter_metadata(metadata: dict) -> dict:
     """Normalize all values in frontmatter metadata dict.
 
@@ -233,9 +249,15 @@ class EntityParser:
 
         content = strip_bom(content)
 
-        # Parse frontmatter with proper error handling for malformed YAML
+        # Parse frontmatter with proper error handling for malformed YAML.
+        # We use frontmatter.parse() instead of frontmatter.loads() because
+        # loads() does Post(content, handler, **metadata), which crashes when
+        # the YAML contains reserved keys like 'content' or 'handler'.
+        # See basic-memory-cloud#375.
         try:
-            post = frontmatter.loads(content)
+            fm_metadata, fm_content = frontmatter.parse(content)
+            post = frontmatter.Post(fm_content)
+            post.metadata.update(fm_metadata)
         except yaml.YAMLError as e:
             logger.warning(
                 f"Failed to parse YAML frontmatter in {file_path}: {e}. "
@@ -248,14 +270,21 @@ class EntityParser:
         # Normalize frontmatter values
         metadata = normalize_frontmatter_metadata(post.metadata)
 
-        # Ensure required fields have defaults
+        # Ensure required string fields are always strings.
+        # YAML can parse these as lists when authors use block sequence syntax
+        # (e.g. "title:\n  - My Title"), causing 'list' has no attribute 'strip'
+        # downstream.  See basic-memory-cloud#376.
         title = metadata.get("title")
+        if title is not None:
+            title = _coerce_to_string(title)
         if not title or title == "None":
             metadata["title"] = file_path.stem
         else:
             metadata["title"] = title
 
         note_type = metadata.get("type")
+        if note_type is not None:
+            note_type = _coerce_to_string(note_type)
         metadata["type"] = note_type if note_type is not None else "note"
 
         tags = parse_tags(metadata.get("tags", []))  # pyright: ignore

src/basic_memory/mcp/async_client.py

@@ -5,6 +5,7 @@ from typing import AsyncIterator, Callable, Optional
 from httpx import ASGITransport, AsyncClient, Timeout
 from loguru import logger
 
+from basic_memory import telemetry
 from basic_memory.api.app import app as fastapi_app
 from basic_memory.config import ConfigManager, ProjectMode
 
@@ -43,21 +44,47 @@ def _asgi_client(timeout: Timeout) -> AsyncClient:
 
 async def _resolve_cloud_token(config) -> str:
     """Resolve cloud token with API key preferred, OAuth fallback."""
-    token = config.cloud_api_key
-    if token:
-        return token
+    with telemetry.span(
+        "routing.resolve_cloud_credentials",
+        has_api_key=bool(config.cloud_api_key),
+    ):
+        token = config.cloud_api_key
+        if token:
+            return token
 
-    from basic_memory.cli.auth import CLIAuth
+        from basic_memory.cli.auth import CLIAuth
 
-    auth = CLIAuth(client_id=config.cloud_client_id, authkit_domain=config.cloud_domain)
-    token = await auth.get_valid_token()
-    if token:
-        return token
+        auth = CLIAuth(client_id=config.cloud_client_id, authkit_domain=config.cloud_domain)
+        token = await auth.get_valid_token()
+        if token:
+            return token
 
-    raise RuntimeError(
-        "Cloud routing requested but no credentials found. "
-        "Run 'bm cloud api-key save <key>' or 'bm cloud login' first."
-    )
+        logger.error("Cloud routing requested but no credentials were available")
+        raise RuntimeError(
+            "Cloud routing requested but no credentials found. "
+            "Run 'bm cloud api-key save <key>' or 'bm cloud login' first."
+        )
+
+
+def resolve_configured_workspace(
+    *,
+    config=None,
+    project_name: Optional[str] = None,
+    workspace: Optional[str] = None,
+) -> Optional[str]:
+    """Resolve workspace from explicit input, per-project config, then global default."""
+    if workspace is not None:
+        return workspace
+
+    if config is None:
+        config = ConfigManager().config
+
+    if project_name is not None:
+        project_entry = config.projects.get(project_name)
+        if project_entry and project_entry.workspace_id:
+            return project_entry.workspace_id
+
+    return config.default_workspace
 
 
 @asynccontextmanager
@@ -82,15 +109,20 @@ async def _cloud_client(
 
 
 @asynccontextmanager
-async def get_cloud_control_plane_client() -> AsyncIterator[AsyncClient]:
+async def get_cloud_control_plane_client(
+    workspace: Optional[str] = None,
+) -> AsyncIterator[AsyncClient]:
     """Create a control-plane cloud client for endpoints outside /proxy."""
     config = ConfigManager().config
     timeout = _build_timeout()
     token = await _resolve_cloud_token(config)
+    headers = {"Authorization": f"Bearer {token}"}
+    if workspace:
+        headers["X-Workspace-ID"] = workspace
     logger.info(f"Creating HTTP client for cloud control plane at: {config.cloud_host}")
     async with AsyncClient(
         base_url=config.cloud_host,
-        headers={"Authorization": f"Bearer {token}"},
+        headers=headers,
         timeout=timeout,
     ) as client:
         yield client
@@ -154,14 +186,19 @@ async def get_client(
     # Outcome: route strictly based on explicit flag.
     if _explicit_routing():
         if _force_local_mode():
-            logger.info("Explicit local routing enabled - using ASGI client")
+            logger.debug("Explicit local routing enabled - using ASGI client")
             async with _asgi_client(timeout) as client:
                 yield client
             return
 
         if _force_cloud_mode():
-            logger.info("Explicit cloud routing enabled - using cloud proxy client")
-            async with _cloud_client(config, timeout, workspace=workspace) as client:
+            logger.debug("Explicit cloud routing enabled - using cloud proxy client")
+            effective_workspace = resolve_configured_workspace(
+                config=config,
+                project_name=project_name,
+                workspace=workspace,
+            )
+            async with _cloud_client(config, timeout, workspace=effective_workspace) as client:
                 yield client
             return
 
@@ -172,9 +209,14 @@ async def get_client(
     if project_name is not None and not _explicit_routing():
         project_mode = config.get_project_mode(project_name)
         if project_mode == ProjectMode.CLOUD:
-            logger.info(f"Project '{project_name}' is cloud mode - using cloud proxy client")
+            logger.debug(f"Project '{project_name}' is cloud mode - using cloud proxy client")
+            effective_workspace = resolve_configured_workspace(
+                config=config,
+                project_name=project_name,
+                workspace=workspace,
+            )
             try:
-                async with _cloud_client(config, timeout, workspace=workspace) as client:
+                async with _cloud_client(config, timeout, workspace=effective_workspace) as client:
                     yield client
             except RuntimeError as exc:
                 raise RuntimeError(
@@ -183,13 +225,13 @@ async def get_client(
                 ) from exc
             return
 
-        logger.info(f"Project '{project_name}' is local mode - using ASGI client")
+        logger.debug(f"Project '{project_name}' is local mode - using ASGI client")
         async with _asgi_client(timeout) as client:
             yield client
         return
 
     # --- Default fallback ---
-    logger.info("Default routing - using ASGI client for local Basic Memory API")
+    logger.debug("Default routing - using ASGI client for local Basic Memory API")
     async with _asgi_client(timeout) as client:
         yield client
 

src/basic_memory/mcp/clients/knowledge.py

@@ -7,6 +7,7 @@ from typing import Any
 
 from httpx import AsyncClient
 
+from basic_memory import telemetry
 from basic_memory.mcp.tools.utils import call_get, call_post, call_put, call_patch, call_delete
 from basic_memory.schemas.response import (
     EntityResponse,
@@ -58,12 +59,21 @@ class KnowledgeClient:
             ToolError: If the request fails
         """
         params = {"fast": fast} if fast is not None else None
-        response = await call_post(
-            self.http_client,
-            f"{self._base_path}/entities",
-            json=entity_data,
-            params=params,
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.create_entity",
+            client_name="knowledge",
+            operation="create_entity",
+            fast=fast,
+        ):
+            response = await call_post(
+                self.http_client,
+                f"{self._base_path}/entities",
+                json=entity_data,
+                params=params,
+                client_name="knowledge",
+                operation="create_entity",
+                path_template="/v2/projects/{project_id}/knowledge/entities",
+            )
         return EntityResponse.model_validate(response.json())
 
     async def update_entity(
@@ -86,12 +96,21 @@ class KnowledgeClient:
             ToolError: If the request fails
         """
         params = {"fast": fast} if fast is not None else None
-        response = await call_put(
-            self.http_client,
-            f"{self._base_path}/entities/{entity_id}",
-            json=entity_data,
-            params=params,
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.update_entity",
+            client_name="knowledge",
+            operation="update_entity",
+            fast=fast,
+        ):
+            response = await call_put(
+                self.http_client,
+                f"{self._base_path}/entities/{entity_id}",
+                json=entity_data,
+                params=params,
+                client_name="knowledge",
+                operation="update_entity",
+                path_template="/v2/projects/{project_id}/knowledge/entities/{entity_id}",
+            )
         return EntityResponse.model_validate(response.json())
 
     async def get_entity(self, entity_id: str) -> EntityResponse:
@@ -106,10 +125,18 @@ class KnowledgeClient:
         Raises:
             ToolError: If the entity is not found or request fails
         """
-        response = await call_get(
-            self.http_client,
-            f"{self._base_path}/entities/{entity_id}",
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.get_entity",
+            client_name="knowledge",
+            operation="get_entity",
+        ):
+            response = await call_get(
+                self.http_client,
+                f"{self._base_path}/entities/{entity_id}",
+                client_name="knowledge",
+                operation="get_entity",
+                path_template="/v2/projects/{project_id}/knowledge/entities/{entity_id}",
+            )
         return EntityResponse.model_validate(response.json())
 
     async def patch_entity(
@@ -132,12 +159,21 @@ class KnowledgeClient:
             ToolError: If the request fails
         """
         params = {"fast": fast} if fast is not None else None
-        response = await call_patch(
-            self.http_client,
-            f"{self._base_path}/entities/{entity_id}",
-            json=patch_data,
-            params=params,
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.patch_entity",
+            client_name="knowledge",
+            operation="patch_entity",
+            fast=fast,
+        ):
+            response = await call_patch(
+                self.http_client,
+                f"{self._base_path}/entities/{entity_id}",
+                json=patch_data,
+                params=params,
+                client_name="knowledge",
+                operation="patch_entity",
+                path_template="/v2/projects/{project_id}/knowledge/entities/{entity_id}",
+            )
         return EntityResponse.model_validate(response.json())
 
     async def delete_entity(self, entity_id: str) -> DeleteEntitiesResponse:
@@ -152,10 +188,18 @@ class KnowledgeClient:
         Raises:
             ToolError: If the entity is not found or request fails
         """
-        response = await call_delete(
-            self.http_client,
-            f"{self._base_path}/entities/{entity_id}",
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.delete_entity",
+            client_name="knowledge",
+            operation="delete_entity",
+        ):
+            response = await call_delete(
+                self.http_client,
+                f"{self._base_path}/entities/{entity_id}",
+                client_name="knowledge",
+                operation="delete_entity",
+                path_template="/v2/projects/{project_id}/knowledge/entities/{entity_id}",
+            )
         return DeleteEntitiesResponse.model_validate(response.json())
 
     async def move_entity(self, entity_id: str, destination_path: str) -> EntityResponse:
@@ -171,11 +215,19 @@ class KnowledgeClient:
         Raises:
             ToolError: If the request fails
         """
-        response = await call_put(
-            self.http_client,
-            f"{self._base_path}/entities/{entity_id}/move",
-            json={"destination_path": destination_path},
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.move_entity",
+            client_name="knowledge",
+            operation="move_entity",
+        ):
+            response = await call_put(
+                self.http_client,
+                f"{self._base_path}/entities/{entity_id}/move",
+                json={"destination_path": destination_path},
+                client_name="knowledge",
+                operation="move_entity",
+                path_template="/v2/projects/{project_id}/knowledge/entities/{entity_id}/move",
+            )
         return EntityResponse.model_validate(response.json())
 
     async def move_directory(
@@ -193,14 +245,22 @@ class KnowledgeClient:
         Raises:
             ToolError: If the request fails
         """
-        response = await call_post(
-            self.http_client,
-            f"{self._base_path}/move-directory",
-            json={
-                "source_directory": source_directory,
-                "destination_directory": destination_directory,
-            },
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.move_directory",
+            client_name="knowledge",
+            operation="move_directory",
+        ):
+            response = await call_post(
+                self.http_client,
+                f"{self._base_path}/move-directory",
+                json={
+                    "source_directory": source_directory,
+                    "destination_directory": destination_directory,
+                },
+                client_name="knowledge",
+                operation="move_directory",
+                path_template="/v2/projects/{project_id}/knowledge/move-directory",
+            )
         return DirectoryMoveResult.model_validate(response.json())
 
     async def delete_directory(self, directory: str) -> DirectoryDeleteResult:
@@ -215,11 +275,19 @@ class KnowledgeClient:
         Raises:
             ToolError: If the request fails
         """
-        response = await call_post(
-            self.http_client,
-            f"{self._base_path}/delete-directory",
-            json={"directory": directory},
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.delete_directory",
+            client_name="knowledge",
+            operation="delete_directory",
+        ):
+            response = await call_post(
+                self.http_client,
+                f"{self._base_path}/delete-directory",
+                json={"directory": directory},
+                client_name="knowledge",
+                operation="delete_directory",
+                path_template="/v2/projects/{project_id}/knowledge/delete-directory",
+            )
         return DirectoryDeleteResult.model_validate(response.json())
 
     # --- Resolution ---
@@ -237,10 +305,18 @@ class KnowledgeClient:
         Raises:
             ToolError: If the identifier cannot be resolved
         """
-        response = await call_post(
-            self.http_client,
-            f"{self._base_path}/resolve",
-            json={"identifier": identifier, "strict": strict},
-        )
+        with telemetry.scope(
+            "mcp.client.knowledge.resolve_entity",
+            client_name="knowledge",
+            operation="resolve_entity",
+        ):
+            response = await call_post(
+                self.http_client,
+                f"{self._base_path}/resolve",
+                json={"identifier": identifier, "strict": strict},
+                client_name="knowledge",
+                operation="resolve_entity",
+                path_template="/v2/projects/{project_id}/knowledge/resolve",
+            )
         data = response.json()
         return data["external_id"]

src/basic_memory/mcp/clients/memory.py

@@ -7,6 +7,7 @@ from typing import Optional
 
 from httpx import AsyncClient
 
+from basic_memory import telemetry
 from basic_memory.mcp.tools.utils import call_get
 from basic_memory.schemas.memory import GraphContext
 
@@ -71,11 +72,21 @@ class MemoryClient:
         if timeframe:
             params["timeframe"] = timeframe
 
-        response = await call_get(
-            self.http_client,
-            f"{self._base_path}/{path}",
-            params=params,
-        )
+        with telemetry.scope(
+            "mcp.client.memory.build_context",
+            client_name="memory",
+            operation="build_context",
+            page=page,
+            page_size=page_size,
+        ):
+            response = await call_get(
+                self.http_client,
+                f"{self._base_path}/{path}",
+                params=params,
+                client_name="memory",
+                operation="build_context",
+                path_template="/v2/projects/{project_id}/memory/{path}",
+            )
         return GraphContext.model_validate(response.json())
 
     async def recent(
@@ -112,9 +123,19 @@ class MemoryClient:
             # Join types as comma-separated string if provided
             params["type"] = ",".join(types) if isinstance(types, list) else types
 
-        response = await call_get(
-            self.http_client,
-            f"{self._base_path}/recent",
-            params=params,
-        )
+        with telemetry.scope(
+            "mcp.client.memory.recent_activity",
+            client_name="memory",
+            operation="recent_activity",
+            page=page,
+            page_size=page_size,
+        ):
+            response = await call_get(
+                self.http_client,
+                f"{self._base_path}/recent",
+                params=params,
+                client_name="memory",
+                operation="recent_activity",
+                path_template="/v2/projects/{project_id}/memory/recent",
+            )
         return GraphContext.model_validate(response.json())

src/basic_memory/mcp/clients/resource.py

@@ -7,6 +7,7 @@ from typing import Optional
 
 from httpx import AsyncClient, Response
 
+from basic_memory import telemetry
 from basic_memory.mcp.tools.utils import call_get
 
 
@@ -64,8 +65,18 @@ class ResourceClient:
         if page_size is not None:
             params["page_size"] = page_size
 
-        return await call_get(
-            self.http_client,
-            f"{self._base_path}/{entity_id}",
-            params=params if params else None,
-        )
+        with telemetry.scope(
+            "mcp.client.resource.read",
+            client_name="resource",
+            operation="read",
+            page=page,
+            page_size=page_size,
+        ):
+            return await call_get(
+                self.http_client,
+                f"{self._base_path}/{entity_id}",
+                params=params if params else None,
+                client_name="resource",
+                operation="read",
+                path_template="/v2/projects/{project_id}/resource/{entity_id}",
+            )

src/basic_memory/mcp/clients/search.py

@@ -7,6 +7,7 @@ from typing import Any
 
 from httpx import AsyncClient
 
+from basic_memory import telemetry
 from basic_memory.mcp.tools.utils import call_post
 from basic_memory.schemas.search import SearchResponse
 
@@ -56,10 +57,20 @@ class SearchClient:
         Raises:
             ToolError: If the request fails
         """
-        response = await call_post(
-            self.http_client,
-            f"{self._base_path}/",
-            json=query,
-            params={"page": page, "page_size": page_size},
-        )
+        with telemetry.scope(
+            "mcp.client.search.search",
+            client_name="search",
+            operation="search",
+            page=page,
+            page_size=page_size,
+        ):
+            response = await call_post(
+                self.http_client,
+                f"{self._base_path}/",
+                json=query,
+                params={"page": page, "page_size": page_size},
+                client_name="search",
+                operation="search",
+                path_template="/v2/projects/{project_id}/search/",
+            )
         return SearchResponse.model_validate(response.json())

src/basic_memory/mcp/project_context.py

@@ -9,7 +9,7 @@ compatibility with existing MCP tools.
 """
 
 from contextlib import asynccontextmanager
-from typing import AsyncIterator, Optional, List, Tuple
+from typing import AsyncIterator, Awaitable, Callable, Optional, List, Tuple
 
 from httpx import AsyncClient
 from httpx._types import (
@@ -19,6 +19,7 @@ from loguru import logger
 from fastmcp import Context
 from mcp.server.fastmcp.exceptions import ToolError
 
+from basic_memory import telemetry
 from basic_memory.config import BasicMemoryConfig, ConfigManager, ProjectMode
 from basic_memory.project_resolver import ProjectResolver
 from basic_memory.schemas.cloud import WorkspaceInfo, WorkspaceListResponse
@@ -27,11 +28,115 @@ from basic_memory.schemas.v2 import ProjectResolveResponse
 from basic_memory.schemas.memory import memory_url_path
 from basic_memory.utils import generate_permalink, normalize_project_reference
 
+# --- Workspace provider injection ---
+# Mirrors the set_client_factory() pattern in async_client.py.
+# The cloud MCP server sets a provider that queries its own database directly,
+# avoiding the control-plane HTTP round-trip that requires local credentials.
+_workspace_provider: Optional[Callable[[], Awaitable[list[WorkspaceInfo]]]] = None
+
+
+def set_workspace_provider(provider: Callable[[], Awaitable[list[WorkspaceInfo]]]) -> None:
+    """Override workspace discovery (for cloud app, testing, etc)."""
+    global _workspace_provider
+    _workspace_provider = provider
+
+
+async def _resolve_default_project_from_api() -> Optional[str]:
+    """Query the projects API for the default project.
+
+    Used as a fallback when ConfigManager has no local config (cloud mode).
+    """
+    from basic_memory.mcp.async_client import get_client
+
+    try:
+        async with get_client() as client:
+            response = await client.get("/v2/projects/")
+            if response.status_code == 200:
+                project_list = ProjectList.model_validate(response.json())
+                if project_list.default_project:
+                    return project_list.default_project
+                # Fallback: find project with is_default=True
+                for p in project_list.projects:
+                    if p.is_default:
+                        return p.name
+    except Exception:
+        pass
+    return None
+
+
+async def _get_cached_active_project(context: Optional[Context]) -> Optional[ProjectItem]:
+    """Return the cached active project from context when available."""
+    if not context:
+        return None
+
+    cached_raw = await context.get_state("active_project")
+    if isinstance(cached_raw, dict):
+        return ProjectItem.model_validate(cached_raw)
+    return None
+
+
+async def _set_cached_active_project(
+    context: Optional[Context],
+    active_project: ProjectItem,
+) -> None:
+    """Persist the active project and known default-project metadata in context."""
+    if not context:
+        return
+
+    await context.set_state("active_project", active_project.model_dump())
+    if active_project.is_default:
+        await context.set_state("default_project_name", active_project.name)
+
+
+async def _get_cached_default_project(context: Optional[Context]) -> Optional[str]:
+    """Return the cached default project name from context when available."""
+    if not context:
+        return None
+
+    cached_default = await context.get_state("default_project_name")
+    if isinstance(cached_default, str):
+        return cached_default
+    return None
+
+
+def _canonicalize_project_name(
+    project_name: Optional[str],
+    config: BasicMemoryConfig,
+) -> Optional[str]:
+    """Return the configured project name when the identifier matches by permalink.
+
+    Project routing happens before API validation, so we normalize explicit inputs
+    here to keep local/cloud routing aligned with the database's case-insensitive
+    project resolver.
+    """
+    if project_name is None:
+        return None
+
+    requested_permalink = generate_permalink(project_name)
+    for configured_name in config.projects:
+        if generate_permalink(configured_name) == requested_permalink:
+            return configured_name
+
+    return project_name
+
+
+def _project_matches_identifier(project_item: ProjectItem, identifier: Optional[str]) -> bool:
+    """Return True when the identifier refers to the cached project."""
+    if identifier is None:
+        return True
+
+    normalized_identifier = generate_permalink(identifier)
+    return normalized_identifier in {
+        generate_permalink(project_item.name),
+        project_item.permalink,
+    }
+
 
 async def resolve_project_parameter(
     project: Optional[str] = None,
     allow_discovery: bool = False,
     default_project: Optional[str] = None,
+    context: Optional[Context] = None,
 ) -> Optional[str]:
     """Resolve project parameter using unified linear priority chain.
 
@@ -54,17 +159,46 @@ async def resolve_project_parameter(
     Returns:
         Resolved project name or None if no resolution possible
     """
-    # Load config for any values not explicitly provided
-    if default_project is None:
+    with telemetry.span(
+        "routing.resolve_project",
+        requested_project=project,
+        allow_discovery=allow_discovery,
+    ):
         config = ConfigManager().config
-        default_project = config.default_project
 
-    # Create resolver with configuration and resolve
-    resolver = ProjectResolver.from_env(
-        default_project=default_project,
-    )
-    result = resolver.resolve(project=project, allow_discovery=allow_discovery)
-    return result.project
+        # Trigger: project already resolved earlier in the same MCP request
+        # Why: the active project is request-constant, so re-discovering the
+        #   default project via /v2/projects/ just repeats work
+        # Outcome: reuse the cached project name as the explicit candidate
+        if project is None:
+            cached_project = await _get_cached_active_project(context)
+            if cached_project is not None:
+                project = cached_project.name
+
+        # Trigger: there is no explicit project after env/context normalization
+        # Why: default-project discovery is only needed as a fallback; doing it
+        #   for explicit requests adds an avoidable /v2/projects/ round-trip
+        # Outcome: skip default lookup when the active project is already known
+        if default_project is None and project is None:
+            # Load config for any values not explicitly provided.
+            # ConfigManager reads from the local config file, which doesn't exist in cloud mode.
+            # When it returns None, fall back to querying the projects API for the is_default flag.
+            default_project = config.default_project
+
+            if default_project is None:
+                default_project = await _get_cached_default_project(context)
+
+            if default_project is None:
+                default_project = await _resolve_default_project_from_api()
+                if default_project and context:
+                    await context.set_state("default_project_name", default_project)
+
+        # Create resolver with configuration and resolve
+        resolver = ProjectResolver.from_env(
+            default_project=default_project,
+        )
+        result = resolver.resolve(project=project, allow_discovery=allow_discovery)
+        return _canonicalize_project_name(result.project, config)
 
 
 async def get_project_names(client: AsyncClient, headers: HeaderTypes | None = None) -> List[str]:
@@ -103,6 +237,19 @@ async def get_available_workspaces(context: Optional[Context] = None) -> list[Wo
         if isinstance(cached_raw, list):
             return [WorkspaceInfo.model_validate(item) for item in cached_raw]
 
+    # Trigger: workspace provider was injected (e.g., by cloud MCP server)
+    # Why: the cloud server IS the cloud — it can query its own database
+    #   directly instead of making an HTTP round-trip that requires local credentials
+    # Outcome: use provider result, cache in context, skip control-plane client
+    if _workspace_provider is not None:
+        workspaces = await _workspace_provider()
+        if context:
+            await context.set_state(
+                "available_workspaces",
+                [ws.model_dump() for ws in workspaces],
+            )
+        return workspaces
+
     from basic_memory.mcp.async_client import get_cloud_control_plane_client
     from basic_memory.mcp.tools.utils import call_get
 
@@ -124,51 +271,60 @@ async def resolve_workspace_parameter(
     context: Optional[Context] = None,
 ) -> WorkspaceInfo:
     """Resolve workspace using explicit input, session cache, and cloud discovery."""
-    if context:
-        cached_raw = await context.get_state("active_workspace")
-        if isinstance(cached_raw, dict):
-            cached_workspace = WorkspaceInfo.model_validate(cached_raw)
-            if workspace is None or _workspace_matches_identifier(cached_workspace, workspace):
-                logger.debug(f"Using cached workspace from context: {cached_workspace.tenant_id}")
-                return cached_workspace
+    with telemetry.scope(
+        "routing.resolve_workspace",
+        workspace_requested=workspace is not None,
+        has_context=context is not None,
+    ):
+        if context:
+            cached_raw = await context.get_state("active_workspace")
+            if isinstance(cached_raw, dict):
+                cached_workspace = WorkspaceInfo.model_validate(cached_raw)
+                if workspace is None or _workspace_matches_identifier(cached_workspace, workspace):
+                    logger.debug(
+                        f"Using cached workspace from context: {cached_workspace.tenant_id}"
+                    )
+                    return cached_workspace
 
-    workspaces = await get_available_workspaces(context=context)
-    if not workspaces:
-        raise ValueError(
-            "No accessible workspaces found for this account. "
-            "Ensure you have an active subscription and tenant access."
-        )
-
-    selected_workspace: WorkspaceInfo | None = None
-
-    if workspace:
-        matches = [item for item in workspaces if _workspace_matches_identifier(item, workspace)]
-        if not matches:
+        workspaces = await get_available_workspaces(context=context)
+        if not workspaces:
             raise ValueError(
-                f"Workspace '{workspace}' was not found.\n"
+                "No accessible workspaces found for this account. "
+                "Ensure you have an active subscription and tenant access."
+            )
+
+        selected_workspace: WorkspaceInfo | None = None
+
+        if workspace:
+            matches = [
+                item for item in workspaces if _workspace_matches_identifier(item, workspace)
+            ]
+            if not matches:
+                raise ValueError(
+                    f"Workspace '{workspace}' was not found.\n"
+                    f"Available workspaces:\n{_workspace_choices(workspaces)}"
+                )
+            if len(matches) > 1:
+                raise ValueError(
+                    f"Workspace name '{workspace}' matches multiple workspaces. "
+                    "Use tenant_id instead.\n"
+                    f"Available workspaces:\n{_workspace_choices(workspaces)}"
+                )
+            selected_workspace = matches[0]
+        elif len(workspaces) == 1:
+            selected_workspace = workspaces[0]
+        else:
+            raise ValueError(
+                "Multiple workspaces are available. Ask the user which workspace to use, then retry "
+                "with the 'workspace' argument set to the tenant_id or unique name.\n"
                 f"Available workspaces:\n{_workspace_choices(workspaces)}"
             )
-        if len(matches) > 1:
-            raise ValueError(
-                f"Workspace name '{workspace}' matches multiple workspaces. "
-                "Use tenant_id instead.\n"
-                f"Available workspaces:\n{_workspace_choices(workspaces)}"
-            )
-        selected_workspace = matches[0]
-    elif len(workspaces) == 1:
-        selected_workspace = workspaces[0]
-    else:
-        raise ValueError(
-            "Multiple workspaces are available. Ask the user which workspace to use, then retry "
-            "with the 'workspace' argument set to the tenant_id or unique name.\n"
-            f"Available workspaces:\n{_workspace_choices(workspaces)}"
-        )
 
-    if context:
-        await context.set_state("active_workspace", selected_workspace.model_dump())
-        logger.debug(f"Cached workspace in context: {selected_workspace.tenant_id}")
+        if context:
+            await context.set_state("active_workspace", selected_workspace.model_dump())
+            logger.debug(f"Cached workspace in context: {selected_workspace.tenant_id}")
 
-    return selected_workspace
+        return selected_workspace
 
 
 async def get_active_project(
@@ -191,53 +347,58 @@ async def get_active_project(
         ValueError: If no project can be resolved
         HTTPError: If project doesn't exist or is inaccessible
     """
-    # Deferred import to avoid circular dependency with tools
-    from basic_memory.mcp.tools.utils import call_post
+    with telemetry.scope(
+        "routing.validate_project",
+        requested_project=project,
+        has_context=context is not None,
+    ):
+        # Deferred import to avoid circular dependency with tools
+        from basic_memory.mcp.tools.utils import call_post
 
-    resolved_project = await resolve_project_parameter(project)
-    if not resolved_project:
-        project_names = await get_project_names(client, headers)
-        raise ValueError(
-            "No project specified. "
-            "Either set 'default_project' in config, or use 'project' argument.\n"
-            f"Available projects: {project_names}"
+        cached_project = await _get_cached_active_project(context)
+        if cached_project and _project_matches_identifier(cached_project, project):
+            logger.debug(f"Using cached project from context: {cached_project.name}")
+            return cached_project
+
+        resolved_project = await resolve_project_parameter(project, context=context)
+        if not resolved_project:
+            project_names = await get_project_names(client, headers)
+            raise ValueError(
+                "No project specified. "
+                "Either set 'default_project' in config, or use 'project' argument.\n"
+                f"Available projects: {project_names}"
+            )
+
+        project = resolved_project
+
+        if cached_project and _project_matches_identifier(cached_project, project):
+            logger.debug(f"Using cached project from context: {cached_project.name}")
+            return cached_project
+
+        # Validate project exists by calling API
+        logger.debug(f"Validating project: {project}")
+        response = await call_post(
+            client,
+            "/v2/projects/resolve",
+            json={"identifier": project},
+            headers=headers,
+        )
+        resolved = ProjectResolveResponse.model_validate(response.json())
+        active_project = ProjectItem(
+            id=resolved.project_id,
+            external_id=resolved.external_id,
+            name=resolved.name,
+            path=resolved.path,
+            is_default=resolved.is_default,
         )
 
-    project = resolved_project
+        # Cache in context if available
+        await _set_cached_active_project(context, active_project)
+        if context:
+            logger.debug(f"Cached project in context: {project}")
 
-    # Check if already cached in context
-    if context:
-        cached_raw = await context.get_state("active_project")
-        if isinstance(cached_raw, dict):
-            cached_project = ProjectItem.model_validate(cached_raw)
-            if cached_project.name == project:
-                logger.debug(f"Using cached project from context: {project}")
-                return cached_project
-
-    # Validate project exists by calling API
-    logger.debug(f"Validating project: {project}")
-    response = await call_post(
-        client,
-        "/v2/projects/resolve",
-        json={"identifier": project},
-        headers=headers,
-    )
-    resolved = ProjectResolveResponse.model_validate(response.json())
-    active_project = ProjectItem(
-        id=resolved.project_id,
-        external_id=resolved.external_id,
-        name=resolved.name,
-        path=resolved.path,
-        is_default=resolved.is_default,
-    )
-
-    # Cache in context if available
-    if context:
-        await context.set_state("active_project", active_project.model_dump())
-        logger.debug(f"Cached project in context: {project}")
-
-    logger.debug(f"Validated project: {active_project.name}")
-    return active_project
+        logger.debug(f"Validated project: {active_project.name}")
+        return active_project
 
 
 def _split_project_prefix(path: str) -> tuple[Optional[str], str]:
@@ -268,66 +429,91 @@ async def resolve_project_and_path(
         Tuple of (active_project, normalized_path, is_memory_url)
     """
     is_memory_url = identifier.strip().startswith("memory://")
-    if not is_memory_url:
-        active_project = await get_active_project(client, project, context, headers)
-        return active_project, identifier, False
+    config = ConfigManager().config
+    include_project = config.permalinks_include_project if is_memory_url else None
+    with telemetry.scope(
+        "routing.resolve_memory_url",
+        is_memory_url=is_memory_url,
+        requested_project=project,
+        include_project_prefix=include_project,
+    ):
+        if not is_memory_url:
+            active_project = await get_active_project(client, project, context, headers)
+            return active_project, identifier, False
 
-    normalized_path = normalize_project_reference(memory_url_path(identifier))
-    project_prefix, remainder = _split_project_prefix(normalized_path)
-    include_project = ConfigManager().config.permalinks_include_project
+        normalized_path = normalize_project_reference(memory_url_path(identifier))
+        project_prefix, remainder = _split_project_prefix(normalized_path)
+        include_project = config.permalinks_include_project
+        # Trigger: memory URL begins with a potential project segment
+        # Why: allow project-scoped memory URLs without requiring a separate project parameter
+        # Outcome: attempt to resolve the prefix as a project and route to it
+        if project_prefix:
+            cached_project = await _get_cached_active_project(context)
+            if cached_project and _project_matches_identifier(cached_project, project_prefix):
+                resolved_project = await resolve_project_parameter(project_prefix, context=context)
+                if resolved_project and generate_permalink(resolved_project) != generate_permalink(
+                    project_prefix
+                ):
+                    raise ValueError(
+                        f"Project is constrained to '{resolved_project}', cannot use '{project_prefix}'."
+                    )
 
-    # Trigger: memory URL begins with a potential project segment
-    # Why: allow project-scoped memory URLs without requiring a separate project parameter
-    # Outcome: attempt to resolve the prefix as a project and route to it
-    if project_prefix:
-        try:
-            from basic_memory.mcp.tools.utils import call_post
-
-            response = await call_post(
-                client,
-                "/v2/projects/resolve",
-                json={"identifier": project_prefix},
-                headers=headers,
-            )
-            resolved = ProjectResolveResponse.model_validate(response.json())
-        except ToolError as exc:
-            if "project not found" not in str(exc).lower():
-                raise
-        else:
-            resolved_project = await resolve_project_parameter(project_prefix)
-            if resolved_project and generate_permalink(resolved_project) != generate_permalink(
-                project_prefix
-            ):
-                raise ValueError(
-                    f"Project is constrained to '{resolved_project}', cannot use '{project_prefix}'."
+                resolved_path = (
+                    f"{cached_project.permalink}/{remainder}" if include_project else remainder
                 )
+                return cached_project, resolved_path, True
 
-            active_project = ProjectItem(
-                id=resolved.project_id,
-                external_id=resolved.external_id,
-                name=resolved.name,
-                path=resolved.path,
-                is_default=resolved.is_default,
-            )
-            if context:
-                await context.set_state("active_project", active_project.model_dump())
+            try:
+                from basic_memory.mcp.tools.utils import call_post
 
-            resolved_path = f"{resolved.permalink}/{remainder}" if include_project else remainder
-            return active_project, resolved_path, True
+                response = await call_post(
+                    client,
+                    "/v2/projects/resolve",
+                    json={"identifier": project_prefix},
+                    headers=headers,
+                )
+                resolved = ProjectResolveResponse.model_validate(response.json())
+            except ToolError as exc:
+                if "project not found" not in str(exc).lower():
+                    raise
+            else:
+                resolved_project = await resolve_project_parameter(project_prefix, context=context)
+                if resolved_project and generate_permalink(resolved_project) != generate_permalink(
+                    project_prefix
+                ):
+                    raise ValueError(
+                        f"Project is constrained to '{resolved_project}', cannot use '{project_prefix}'."
+                    )
 
-    # Trigger: no resolvable project prefix in the memory URL
-    # Why: preserve existing memory URL behavior within the active project
-    # Outcome: use the active project and normalize the path for lookup
-    active_project = await get_active_project(client, project, context, headers)
-    resolved_path = normalized_path
-    if include_project:
-        # Trigger: project-prefixed permalinks are enabled and the path lacks a prefix
-        # Why: ensure memory URL lookups align with canonical permalinks
-        # Outcome: prefix the path with the active project's permalink
-        project_prefix = active_project.permalink
-        if resolved_path != project_prefix and not resolved_path.startswith(f"{project_prefix}/"):
-            resolved_path = f"{project_prefix}/{resolved_path}"
-    return active_project, resolved_path, True
+                active_project = ProjectItem(
+                    id=resolved.project_id,
+                    external_id=resolved.external_id,
+                    name=resolved.name,
+                    path=resolved.path,
+                    is_default=resolved.is_default,
+                )
+                await _set_cached_active_project(context, active_project)
+
+                resolved_path = (
+                    f"{resolved.permalink}/{remainder}" if include_project else remainder
+                )
+                return active_project, resolved_path, True
+
+        # Trigger: no resolvable project prefix in the memory URL
+        # Why: preserve existing memory URL behavior within the active project
+        # Outcome: use the active project and normalize the path for lookup
+        active_project = await get_active_project(client, project, context, headers)
+        resolved_path = normalized_path
+        if include_project:
+            # Trigger: project-prefixed permalinks are enabled and the path lacks a prefix
+            # Why: ensure memory URL lookups align with canonical permalinks
+            # Outcome: prefix the path with the active project's permalink
+            project_prefix = active_project.permalink
+            if resolved_path != project_prefix and not resolved_path.startswith(
+                f"{project_prefix}/"
+            ):
+                resolved_path = f"{project_prefix}/{resolved_path}"
+        return active_project, resolved_path, True
 
 
 def add_project_metadata(result: str, project_name: str) -> str:
@@ -419,10 +605,11 @@ async def get_project_client(
         _explicit_routing,
         _force_local_mode,
         get_client,
+        is_factory_mode,
     )
 
     # Step 1: Resolve project name from config (no network call)
-    resolved_project = await resolve_project_parameter(project)
+    resolved_project = await resolve_project_parameter(project, context=context)
     if not resolved_project:
         # Fall back to local client to discover projects and raise helpful error
         async with get_client() as client:
@@ -433,14 +620,41 @@ async def get_project_client(
                 f"Available projects: {project_names}"
             )
 
+    # Step 1b: Factory injection (in-process cloud server)
+    # Trigger: set_client_factory() was called (e.g., by cloud MCP server)
+    # Why: the transport layer already resolved workspace and tenant context;
+    #   attempting cloud workspace resolution here would call the production
+    #   control-plane API with no valid credentials and fail with 401
+    # Outcome: use the factory client directly, skip workspace resolution
+    if is_factory_mode():
+        route_mode = "factory"
+        with telemetry.scope(
+            "routing.client_session",
+            project_name=resolved_project,
+            route_mode=route_mode,
+            workspace_id=workspace,
+        ):
+            logger.debug("Using injected client factory for project routing")
+            async with get_client() as client:
+                active_project = await get_active_project(client, resolved_project, context)
+                yield client, active_project
+        return
+
     # Step 2: Check explicit routing BEFORE workspace resolution
     # Trigger: CLI passed --local or --cloud
     # Why: explicit flags must be deterministic — skip workspace entirely for --local
     # Outcome: route strictly based on explicit flag, no workspace network calls
     if _explicit_routing() and _force_local_mode():
-        async with get_client(project_name=resolved_project) as client:
-            active_project = await get_active_project(client, resolved_project, context)
-            yield client, active_project
+        route_mode = "explicit_local"
+        with telemetry.scope(
+            "routing.client_session",
+            project_name=resolved_project,
+            route_mode=route_mode,
+        ):
+            logger.debug("Explicit local routing selected for project client")
+            async with get_client(project_name=resolved_project) as client:
+                active_project = await get_active_project(client, resolved_project, context)
+                yield client, active_project
         return
 
     # Step 3: Determine if cloud routing is needed
@@ -469,28 +683,51 @@ async def get_project_client(
         if effective_workspace is None and config.default_workspace:
             effective_workspace = config.default_workspace
 
+        route_mode = "cloud_proxy"
+
         # Priorities 4-6: if still unresolved, fall back to resolve_workspace_parameter
         # which checks context cache, auto-selects single workspace, or errors
         if effective_workspace is not None:
             # Config-resolved workspace — pass directly to get_client, skip network lookup
-            async with get_client(
+            with telemetry.scope(
+                "routing.client_session",
                 project_name=resolved_project,
-                workspace=effective_workspace,
-            ) as client:
-                active_project = await get_active_project(client, resolved_project, context)
-                yield client, active_project
+                route_mode=route_mode,
+                workspace_id=effective_workspace,
+            ):
+                logger.debug("Using configured workspace for cloud project routing")
+                async with get_client(
+                    project_name=resolved_project,
+                    workspace=effective_workspace,
+                ) as client:
+                    active_project = await get_active_project(client, resolved_project, context)
+                    yield client, active_project
         else:
             # No config-based workspace — use resolve_workspace_parameter for discovery
             active_ws = await resolve_workspace_parameter(workspace=None, context=context)
-            async with get_client(
+            with telemetry.scope(
+                "routing.client_session",
                 project_name=resolved_project,
-                workspace=active_ws.tenant_id,
-            ) as client:
-                active_project = await get_active_project(client, resolved_project, context)
-                yield client, active_project
+                route_mode=route_mode,
+                workspace_id=active_ws.tenant_id,
+            ):
+                logger.debug("Resolved workspace dynamically for cloud project routing")
+                async with get_client(
+                    project_name=resolved_project,
+                    workspace=active_ws.tenant_id,
+                ) as client:
+                    active_project = await get_active_project(client, resolved_project, context)
+                    yield client, active_project
         return
 
     # Step 4: Local routing (default)
-    async with get_client(project_name=resolved_project) as client:
-        active_project = await get_active_project(client, resolved_project, context)
-        yield client, active_project
+    route_mode = "local_asgi"
+    with telemetry.scope(
+        "routing.client_session",
+        project_name=resolved_project,
+        route_mode=route_mode,
+    ):
+        logger.debug("Using default local ASGI routing for project client")
+        async with get_client(project_name=resolved_project) as client:
+            active_project = await get_active_project(client, resolved_project, context)
+            yield client, active_project

src/basic_memory/mcp/prompts/continue_conversation.py

@@ -13,7 +13,6 @@ from pydantic import Field
 from basic_memory.mcp.server import mcp
 from basic_memory.mcp.tools.recent_activity import recent_activity
 from basic_memory.mcp.tools.search import search_notes
-from basic_memory.schemas.search import SearchResponse
 
 
 @mcp.prompt(
@@ -42,15 +41,12 @@ async def continue_conversation(
     logger.info(f"Continuing session, topic: {topic}, timeframe: {timeframe}")
 
     if topic:
-        # Search for the topic using the search tool directly
-        result = await search_notes(query=topic, after_date=timeframe)
+        # Use json format to get structured data for result counting and branching
+        result = await search_notes(query=topic, after_date=timeframe, output_format="json")
 
-        if isinstance(result, SearchResponse):
-            context_text = _format_continuation_results(result, topic)
-            result_count = len(result.results)
-        elif isinstance(result, dict):
+        if isinstance(result, dict):
             results = result.get("results", [])
-            context_text = str(result)
+            context_text = _format_continuation_results(results, topic)
             result_count = len(results)
         else:
             # Error string
@@ -111,23 +107,24 @@ async def continue_conversation(
     return prompt
 
 
-def _format_continuation_results(result: SearchResponse, topic: str) -> str:
-    """Format search results for conversation continuation context."""
-    if not result.results:
+def _format_continuation_results(results: list[dict], topic: str) -> str:
+    """Format search result dicts for conversation continuation context."""
+    if not results:
         return f"No previous context found for '{topic}'."
 
     lines = [f"## Previous Context for '{topic}'\n"]
 
-    for item in result.results:
-        title = item.title or "Untitled"
-        permalink = item.permalink or ""
+    for item in results:
+        title = item.get("title", "Untitled")
+        permalink = item.get("permalink", "")
 
         lines.append(f"### {title}")
         if permalink:
             lines.append(f"permalink: {permalink}")
-            lines.append(f"Read with: `read_note(\"{permalink}\")`")
-        if item.content:
-            content = item.content[:300] + "..." if len(item.content) > 300 else item.content
+            lines.append(f'Read with: `read_note("{permalink}")`')
+        content = item.get("content")
+        if content:
+            content = content[:300] + "..." if len(content) > 300 else content
             lines.append(f"\n{content}")
         lines.append("")
 

src/basic_memory/mcp/prompts/search.py

@@ -11,7 +11,6 @@ from pydantic import Field
 
 from basic_memory.mcp.server import mcp
 from basic_memory.mcp.tools.search import search_notes
-from basic_memory.schemas.search import SearchResponse
 
 
 @mcp.prompt(
@@ -39,18 +38,14 @@ async def search_prompt(
     """
     logger.info(f"Searching knowledge base, query: {query}, timeframe: {timeframe}")
 
-    # Call the search tool directly — it returns SearchResponse, dict, or error string
-    result = await search_notes(query=query, after_date=timeframe)
+    # Use json format to get structured data for result counting and formatting
+    result = await search_notes(query=query, after_date=timeframe, output_format="json")
 
     # Format the tool output into a prompt with guidance
-    if isinstance(result, SearchResponse):
-        result_count = len(result.results)
-        result_text = _format_search_results(result, query)
-    elif isinstance(result, dict):
-        # json output format
+    if isinstance(result, dict):
         results = result.get("results", [])
         result_count = len(results)
-        result_text = str(result)
+        result_text = _format_search_results(results, query)
     else:
         # Error string from search tool
         result_count = 0
@@ -76,28 +71,27 @@ async def search_prompt(
     """)
 
 
-def _format_search_results(result: SearchResponse, query: str) -> str:
-    """Format SearchResponse into readable markdown."""
-    if not result.results:
+def _format_search_results(results: list[dict], query: str) -> str:
+    """Format search result dicts into readable markdown."""
+    if not results:
         return f"No results found for '{query}'."
 
-    lines = [f"Found {len(result.results)} results:\n"]
+    lines = [f"Found {len(results)} results:\n"]
 
-    for item in result.results:
-        title = item.title or "Untitled"
-        permalink = item.permalink or ""
-        score = f" (score: {item.score:.2f})" if item.score else ""
+    for item in results:
+        title = item.get("title", "Untitled")
+        permalink = item.get("permalink", "")
+        score = item.get("score")
+        score_text = f" (score: {score:.2f})" if score else ""
 
-        lines.append(f"- **{title}**{score}")
+        lines.append(f"- **{title}**{score_text}")
         if permalink:
             lines.append(f"  permalink: {permalink}")
-        if item.content:
+        content = item.get("content")
+        if content:
             # Truncate content snippet
-            content = item.content[:200] + "..." if len(item.content) > 200 else item.content
+            content = content[:200] + "..." if len(content) > 200 else content
             lines.append(f"  {content}")
         lines.append("")
 
-    if result.has_more:
-        lines.append("*More results available. Use page=2 to see next page.*")
-
     return "\n".join(lines)

src/basic_memory/mcp/resources/ai_assistant_guide.md

@@ -57,6 +57,16 @@ await write_note(
 )
 ```
 
+> **Important**: `write_note` errors if the note already exists. Use `edit_note` for incremental changes, or pass `overwrite=True` to replace.
+
+```python
+# Preferred: update an existing note incrementally
+await edit_note(identifier="Topic", operation="append", content="\n- [category] new fact")
+
+# Alternative: replace the entire note
+await write_note(title="Topic", content="...", folder="notes", overwrite=True)
+```
+
 ### Reading Knowledge
 
 ```python
@@ -70,11 +80,27 @@ content = await read_note("memory://folder/topic", project="main")
 ### Searching
 
 ```python
+# Basic text search
+results = await search_notes(query="authentication", project="main")
+
+# Search types: "text" (default), "title", "permalink", "vector"/"semantic", "hybrid"
+# Default is "hybrid" when semantic search is enabled, "text" otherwise
+results = await search_notes(query="auth flow", search_type="hybrid")
+
+# Tag shorthand in query (multiple tags: "tag:x AND tag:y" or "tag:x tag:y")
+results = await search_notes(query="tag:security")
+results = await search_notes(query="tag:coffee AND tag:brewing")
+
+# Filter-only search (no query needed)
+results = await search_notes(tags=["security", "auth"], status="active")
+
+# Metadata filters with operators: $in, $gt, $gte, $lt, $lte, $between
 results = await search_notes(
-    query="authentication",
-    project="main",
-    page_size=10
+    metadata_filters={"priority": {"$in": ["high", "critical"]}}
 )
+
+# Override similarity threshold for vector/hybrid search
+results = await search_notes(query="auth", search_type="hybrid", min_similarity=0.5)
 ```
 
 ### Building Context
@@ -162,6 +188,8 @@ activity = await recent_activity(project="main")
 - 2-3 relations per note
 - Meaningful categories and relation types
 
+**Prefer `edit_note` for updates** — use `write_note` only for new notes.
+
 **Search before creating:**
 ```python
 # Find existing entities to reference
@@ -201,6 +229,14 @@ except:
     results = await search_notes(query="test", project=projects[0].name)
 ```
 
+**Note already exists:**
+```python
+# write_note returns an error if the note exists — use edit_note or overwrite
+await edit_note(identifier="Existing Topic", operation="append", content="\n- [update] new info")
+# Or replace entirely:
+await write_note(title="Existing Topic", content="...", folder="notes", overwrite=True)
+```
+
 **Forward references:**
 ```python
 # Check response for unresolved relations
@@ -256,13 +292,14 @@ context = await build_context(url=f"memory://{results[0].permalink}", project="m
 
 | Tool | Purpose | Key Params |
 |------|---------|------------|
-| `write_note` | Create/update | title, content, folder, project |
+| `write_note` | Create new | title, content, folder, project, overwrite |
 | `read_note` | Read content | identifier, project |
 | `edit_note` | Modify existing | identifier, operation, content, project |
-| `search_notes` | Find notes | query, project |
+| `search_notes` | Find notes | query, search_type, tags, metadata_filters, project |
 | `build_context` | Graph traversal | url, depth, project |
 | `recent_activity` | Recent changes | timeframe, project |
 | `list_memory_projects` | Show projects | (none) |
+| `list_workspaces` | Show workspaces | (none) |
 
 ## memory:// URL Format
 
@@ -270,6 +307,7 @@ context = await build_context(url=f"memory://{results[0].permalink}", project="m
 - `memory://folder/title` - By folder + title
 - `memory://permalink` - By permalink
 - `memory://folder/*` - All in folder
+- `memory://project-name/folder/title` - Cross-project (auto-routes to the correct project)
 
 For full documentation: https://docs.basicmemory.com
 

src/basic_memory/mcp/server.py

@@ -2,16 +2,70 @@
 Basic Memory FastMCP server.
 """
 
+import asyncio
 import time
 from contextlib import asynccontextmanager
 
 from fastmcp import FastMCP
 from loguru import logger
+from sqlalchemy import text
+from sqlalchemy.ext.asyncio import async_sessionmaker, AsyncSession
 
 from basic_memory import db
 from basic_memory.cli.auth import CLIAuth
+from basic_memory.config import BasicMemoryConfig
+from basic_memory.db import (
+    scoped_session,
+    _needs_semantic_embedding_backfill,
+    _run_semantic_embedding_backfill,
+)
 from basic_memory.mcp.container import McpContainer, set_container
 from basic_memory.services.initialization import initialize_app
+from basic_memory import telemetry
+
+
+async def _log_embedding_status(session_maker: async_sessionmaker[AsyncSession]) -> None:
+    """Log a clear summary of semantic embedding status at startup."""
+    try:
+        async with scoped_session(session_maker) as session:
+            entity_count = (
+                await session.execute(text("SELECT COUNT(*) FROM entity"))
+            ).scalar() or 0
+            chunk_count = (
+                await session.execute(text("SELECT COUNT(*) FROM search_vector_chunks"))
+            ).scalar() or 0
+            embedding_count = (
+                await session.execute(text("SELECT COUNT(*) FROM search_vector_embeddings_rowids"))
+            ).scalar() or 0
+
+        if entity_count == 0:
+            logger.info("Semantic embeddings: no entities yet")
+        elif embedding_count == 0:
+            logger.warning(
+                f"Semantic embeddings: EMPTY — {entity_count} entities have no embeddings. "
+                "Backfill running in background..."
+            )
+        else:
+            logger.info(
+                f"Semantic embeddings: {embedding_count} embeddings "
+                f"across {chunk_count} chunks for {entity_count} entities"
+            )
+    except Exception as exc:
+        logger.debug(f"Could not check embedding status at startup: {exc}")
+
+
+async def _background_embedding_backfill(
+    config: BasicMemoryConfig,
+    session_maker: async_sessionmaker[AsyncSession],
+) -> None:
+    """Run semantic embedding backfill in the background without blocking startup."""
+    try:
+        if await _needs_semantic_embedding_backfill(config, session_maker):
+            logger.info("Background embedding backfill starting...")
+            await _run_semantic_embedding_backfill(config, session_maker)
+            await _log_embedding_status(session_maker)
+    except Exception as exc:
+        logger.error(f"Background embedding backfill failed: {exc}")
 
 
 @asynccontextmanager
@@ -29,64 +83,96 @@ async def lifespan(app: FastMCP):
     set_container(container)
 
     config = container.config
-    logger.info(f"Starting Basic Memory MCP server (mode={container.mode.name})")
-    logger.info(
-        f"Config: database_backend={config.database_backend.value}, "
-        f"semantic_search_enabled={config.semantic_search_enabled}, "
-        f"default_project={config.default_project}"
-    )
-    if config.semantic_search_enabled:
+    with telemetry.operation(
+        "mcp.lifecycle.startup",
+        entrypoint="mcp",
+        mode=container.mode.name.lower(),
+        default_project=config.default_project,
+    ):
+        logger.info(f"Starting Basic Memory MCP server (mode={container.mode.name})")
         logger.info(
-            f"Semantic search: provider={config.semantic_embedding_provider}, "
-            f"model={config.semantic_embedding_model}, "
-            f"dimensions={config.semantic_embedding_dimensions or 'auto'}, "
-            f"batch_size={config.semantic_embedding_batch_size}"
+            f"Config: database_backend={config.database_backend.value}, "
+            f"semantic_search_enabled={config.semantic_search_enabled}, "
+            f"default_project={config.default_project}"
         )
+        if config.semantic_search_enabled:
+            logger.info(
+                f"Semantic search: provider={config.semantic_embedding_provider}, "
+                f"model={config.semantic_embedding_model}, "
+                f"dimensions={config.semantic_embedding_dimensions or 'auto'}, "
+                f"batch_size={config.semantic_embedding_batch_size}"
+            )
 
-    # Log configured projects with their routing mode
-    for name, entry in config.projects.items():
-        default = " (default)" if name == config.default_project else ""
-        logger.info(f"Project: {name} -> {entry.path} [mode={entry.mode.value}]{default}")
+        # Log configured projects with their routing mode
+        for name, entry in config.projects.items():
+            default = " (default)" if name == config.default_project else ""
+            logger.info(f"Project: {name} -> {entry.path} [mode={entry.mode.value}]{default}")
 
-    # Check cloud auth status (local file check, no network call)
-    auth = CLIAuth(client_id=config.cloud_client_id, authkit_domain=config.cloud_domain)
-    tokens = auth.load_tokens()
-    if tokens is not None:
-        if not auth.is_token_valid(tokens):
-            expires_at = tokens.get("expires_at", 0)
-            expired_ago = int(time.time() - expires_at)
-            logger.warning(f"Cloud token expired {expired_ago}s ago - may need 'bm cloud login'")
-        else:
-            logger.info("Cloud: authenticated (OAuth token valid)")
+        # Check cloud auth status (local file check, no network call)
+        auth = CLIAuth(client_id=config.cloud_client_id, authkit_domain=config.cloud_domain)
+        tokens = auth.load_tokens()
+        if tokens is not None:
+            if not auth.is_token_valid(tokens):
+                expires_at = tokens.get("expires_at", 0)
+                expired_ago = int(time.time() - expires_at)
+                logger.warning(
+                    f"Cloud token expired {expired_ago}s ago - may need 'bm cloud login'"
+                )
+            else:
+                logger.info("Cloud: authenticated (OAuth token valid)")
 
-    if config.cloud_api_key:
-        logger.info("Cloud: API key configured")
+        if config.cloud_api_key:
+            logger.info("Cloud: API key configured")
 
-    # Track if we created the engine (vs test fixtures providing it)
-    # This prevents disposing an engine provided by test fixtures when
-    # multiple Client connections are made in the same test
-    engine_was_none = db._engine is None
+        # Track if we created the engine (vs test fixtures providing it)
+        # This prevents disposing an engine provided by test fixtures when
+        # multiple Client connections are made in the same test
+        engine_was_none = db._engine is None
 
-    # Initialize app (runs migrations, reconciles projects)
-    await initialize_app(container.config)
+        # Initialize app (runs migrations, reconciles projects)
+        await initialize_app(container.config)
 
-    # Create and start sync coordinator (lifecycle centralized in coordinator)
-    sync_coordinator = container.create_sync_coordinator()
-    await sync_coordinator.start()
+        # Log embedding status so it's easy to spot in the logs
+        backfill_task: asyncio.Task | None = None  # type: ignore[type-arg]
+        if config.semantic_search_enabled and db._session_maker is not None:
+            await _log_embedding_status(db._session_maker)
+            # Launch backfill in background so MCP server is ready immediately
+            backfill_task = asyncio.create_task(
+                _background_embedding_backfill(config, db._session_maker),
+                name="embedding-backfill",
+            )
+
+        # Create and start sync coordinator (lifecycle centralized in coordinator)
+        sync_coordinator = container.create_sync_coordinator()
+        await sync_coordinator.start()
 
     try:
         yield
     finally:
         # Shutdown - coordinator handles clean task cancellation
-        logger.debug("Shutting down Basic Memory MCP server")
-        await sync_coordinator.stop()
+        with telemetry.operation(
+            "mcp.lifecycle.shutdown",
+            entrypoint="mcp",
+            mode=container.mode.name.lower(),
+        ):
+            logger.debug("Shutting down Basic Memory MCP server")
 
-        # Only shutdown DB if we created it (not if test fixture provided it)
-        if engine_was_none:
-            await db.shutdown_db()
-            logger.debug("Database connections closed")
-        else:  # pragma: no cover
-            logger.debug("Skipping DB shutdown - engine provided externally")
+            # Cancel embedding backfill if still running
+            if backfill_task is not None and not backfill_task.done():
+                backfill_task.cancel()
+                try:
+                    await backfill_task
+                except asyncio.CancelledError:
+                    logger.info("Background embedding backfill cancelled during shutdown")
+
+            await sync_coordinator.stop()
+
+            # Only shutdown DB if we created it (not if test fixture provided it)
+            if engine_was_none:
+                await db.shutdown_db()
+                logger.debug("Database connections closed")
+            else:  # pragma: no cover
+                logger.debug("Skipping DB shutdown - engine provided externally")
 
 
 mcp = FastMCP(

src/basic_memory/mcp/tools/__init__.py

@@ -18,7 +18,7 @@ from basic_memory.mcp.tools.view_note import view_note
 from basic_memory.mcp.tools.write_note import write_note
 from basic_memory.mcp.tools.cloud_info import cloud_info
 from basic_memory.mcp.tools.release_notes import release_notes
-from basic_memory.mcp.tools.search import search_notes, search_by_metadata
+from basic_memory.mcp.tools.search import search_notes
 from basic_memory.mcp.tools.canvas import canvas
 from basic_memory.mcp.tools.list_directory import list_directory
 from basic_memory.mcp.tools.edit_note import edit_note
@@ -58,7 +58,6 @@ __all__ = [
     "schema_infer",
     "schema_validate",
     "search",
-    "search_by_metadata",
     "search_notes",
     # "search_notes_ui",
     "view_note",

src/basic_memory/mcp/tools/build_context.py

@@ -6,6 +6,7 @@ from loguru import logger
 from fastmcp import Context
 
 from basic_memory.config import ConfigManager
+from basic_memory import telemetry
 from basic_memory.mcp.project_context import (
     detect_project_from_url_prefix,
     get_project_client,
@@ -22,74 +23,6 @@ from basic_memory.schemas.memory import (
     RelationSummary,
 )
 
-# --- Fields to strip from each model (redundant with parent entity) ---
-
-_OBSERVATION_STRIP = {
-    "observation_id",
-    "entity_id",
-    "entity_external_id",
-    "title",
-    "file_path",
-    "created_at",
-}
-_RELATION_STRIP = {
-    "relation_id",
-    "entity_id",
-    "from_entity_id",
-    "from_entity_external_id",
-    "to_entity_id",
-    "to_entity_external_id",
-    "title",
-    "file_path",
-    "created_at",
-}
-_ENTITY_STRIP = {"entity_id", "created_at"}
-_METADATA_STRIP = {"total_results", "generated_at"}
-
-
-def _slim_summary(summary: EntitySummary | RelationSummary | ObservationSummary) -> dict:
-    """Strip redundant fields from a summary model based on its type."""
-    if isinstance(summary, ObservationSummary):
-        strip = _OBSERVATION_STRIP
-    elif isinstance(summary, RelationSummary):
-        strip = _RELATION_STRIP
-    else:
-        strip = _ENTITY_STRIP
-
-    data = summary.model_dump()
-    for key in strip:
-        data.pop(key, None)
-    return data
-
-
-def _slim_context(graph: GraphContext) -> dict:
-    """Transform GraphContext into a slimmed dict, stripping redundant fields.
-
-    Reduces payload size ~40% by removing fields on nested objects that
-    duplicate information already present on the parent entity (IDs,
-    timestamps, file paths).
-    """
-    slimmed_results = []
-    for result in graph.results:
-        slimmed_results.append(
-            {
-                "primary_result": _slim_summary(result.primary_result),
-                "observations": [_slim_summary(obs) for obs in result.observations],
-                "related_results": [_slim_summary(rel) for rel in result.related_results],
-            }
-        )
-
-    metadata = graph.metadata.model_dump()
-    for key in _METADATA_STRIP:
-        metadata.pop(key, None)
-
-    return {
-        "results": slimmed_results,
-        "metadata": metadata,
-        "page": graph.page,
-        "page_size": graph.page_size,
-    }
-
 
 def _format_entity_block(result: ContextResult) -> str:
     """Format a single context result as a markdown block."""
@@ -194,7 +127,7 @@ def _format_context_markdown(graph: GraphContext, project: str) -> str:
     - Or standard formats like "7d", "24h"
 
     Format options:
-    - "json" (default): Slimmed JSON with redundant fields removed
+    - "json" (default): Structured JSON with internal fields excluded
     - "text": Compact markdown text for LLM consumption
     """,
     annotations={"readOnlyHint": True, "openWorldHint": False},
@@ -231,12 +164,12 @@ async def build_context(
         page: Page number of results to return (default: 1)
         page_size: Number of results to return per page (default: 10)
         max_related: Maximum number of related results to return (default: 10)
-        output_format: Response format - "json" for slimmed JSON dict,
+        output_format: Response format - "json" for structured JSON dict,
             "text" for compact markdown text
         context: Optional FastMCP context for performance caching.
 
     Returns:
-        dict (output_format="json"): Slimmed JSON with redundant fields removed
+        dict (output_format="json"): Structured JSON with internal fields excluded
         str (output_format="text"): Compact markdown representation
 
     Examples:
@@ -258,8 +191,6 @@ async def build_context(
         if detected:
             project = detected
 
-    logger.info(f"Building context from {url} in project {project}")
-
     # Convert string depth to integer if needed
     if isinstance(depth, str):
         try:
@@ -271,25 +202,62 @@ async def build_context(
 
     # URL is already validated and normalized by MemoryUrl type annotation
 
-    async with get_project_client(project, workspace, context) as (client, active_project):
-        # Resolve memory:// identifier with project-prefix awareness
-        _, resolved_path, _ = await resolve_project_and_path(client, url, project, context)
+    with telemetry.operation(
+        "mcp.tool.build_context",
+        entrypoint="mcp",
+        tool_name="build_context",
+        requested_project=project,
+        workspace_id=workspace,
+        depth=depth or 1,
+        timeframe=timeframe,
+        page=page,
+        page_size=page_size,
+        max_related=max_related,
+        output_format=output_format,
+        is_memory_url=str(url).startswith("memory://"),
+    ):
+        async with get_project_client(project, workspace, context) as (client, active_project):
+            with telemetry.contextualize(
+                project_name=active_project.name,
+                workspace_id=workspace,
+                tool_name="build_context",
+            ):
+                logger.info(
+                    f"MCP tool call tool=build_context project={active_project.name} "
+                    f"url={url} depth={depth} timeframe={timeframe} output_format={output_format}"
+                )
 
-        # Import here to avoid circular import
-        from basic_memory.mcp.clients import MemoryClient
+                # Resolve memory:// identifier with project-prefix awareness
+                _, resolved_path, _ = await resolve_project_and_path(
+                    client,
+                    url,
+                    active_project.name,
+                    context,
+                )
 
-        # Use typed MemoryClient for API calls
-        memory_client = MemoryClient(client, active_project.external_id)
-        graph = await memory_client.build_context(
-            resolved_path,
-            depth=depth or 1,
-            timeframe=timeframe,
-            page=page,
-            page_size=page_size,
-            max_related=max_related,
-        )
+                # Import here to avoid circular import
+                from basic_memory.mcp.clients import MemoryClient
 
-        if output_format == "text":
-            return _format_context_markdown(graph, active_project.name)
+                # Use typed MemoryClient for API calls
+                memory_client = MemoryClient(client, active_project.external_id)
+                graph = await memory_client.build_context(
+                    resolved_path,
+                    depth=depth or 1,
+                    timeframe=timeframe,
+                    page=page,
+                    page_size=page_size,
+                    max_related=max_related,
+                )
 
-        return _slim_context(graph)
+                logger.info(
+                    f"MCP tool response: tool=build_context project={active_project.name} "
+                    f"uri={graph.metadata.uri or resolved_path} "
+                    f"primary_count={graph.metadata.primary_count or 0} "
+                    f"related_count={graph.metadata.related_count or 0} "
+                    f"output_format={output_format}"
+                )
+
+                if output_format == "text":
+                    return _format_context_markdown(graph, active_project.name)
+
+                return graph.model_dump()

src/basic_memory/mcp/tools/canvas.py

@@ -4,12 +4,14 @@ This tool creates Obsidian canvas files (.canvas) using the JSON Canvas 1.0 spec
 """
 
 import json
-from typing import Dict, List, Any, Optional
+from typing import Annotated, Dict, List, Any, Optional
 
 from loguru import logger
 from fastmcp import Context
+from pydantic import BeforeValidator
 
 from basic_memory.mcp.project_context import get_project_client
+from basic_memory.utils import coerce_list
 from basic_memory.mcp.server import mcp
 from basic_memory.mcp.tools.utils import call_put, call_post, resolve_entity_id
 
@@ -19,8 +21,8 @@ from basic_memory.mcp.tools.utils import call_put, call_post, resolve_entity_id
     annotations={"destructiveHint": False, "idempotentHint": True, "openWorldHint": False},
 )
 async def canvas(
-    nodes: List[Dict[str, Any]],
-    edges: List[Dict[str, Any]],
+    nodes: Annotated[List[Dict[str, Any]], BeforeValidator(coerce_list)],
+    edges: Annotated[List[Dict[str, Any]], BeforeValidator(coerce_list)],
     title: str,
     directory: str,
     project: Optional[str] = None,

src/basic_memory/mcp/tools/chatgpt_tools.py

@@ -7,13 +7,13 @@ a list containing a single `{"type": "text", "text": "{...json...}"}` item.
 
 import json
 from typing import Any, Dict, List, Optional
-from loguru import logger
+
 from fastmcp import Context
+from loguru import logger
 
 from basic_memory.mcp.server import mcp
-from basic_memory.mcp.tools.search import search_notes
 from basic_memory.mcp.tools.read_note import read_note
-from basic_memory.config import ConfigManager
+from basic_memory.mcp.tools.search import search_notes
 from basic_memory.schemas.search import SearchResponse, SearchResult
 
 
@@ -113,16 +113,12 @@ async def search(
     logger.info(f"ChatGPT search request: query='{query}'")
 
     try:
-        # ChatGPT tools don't expose project parameter, so use default project
-        config = ConfigManager().config
-        default_project = config.default_project
-
-        # Call underlying search_notes with sensible defaults for ChatGPT
+        # Let search_notes resolve the default project via get_project_client(),
+        # which works in both local mode (ConfigManager) and cloud mode (database).
         results = await search_notes(
             query=query,
-            project=default_project,  # Use default project for ChatGPT
             page=1,
-            page_size=10,  # Reasonable default for ChatGPT consumption
+            page_size=10,
             output_format="json",
             context=context,
         )
@@ -180,17 +176,13 @@ async def fetch(
     logger.info(f"ChatGPT fetch request: id='{id}'")
 
     try:
-        # ChatGPT tools don't expose project parameter, so use default project
-        config = ConfigManager().config
-        default_project = config.default_project
-
-        # Call underlying read_note function (default output_format="text" returns str)
+        # Let read_note resolve the default project via get_project_client(),
+        # which works in both local mode (ConfigManager) and cloud mode (database).
         content = str(
             await read_note(
                 identifier=id,
-                project=default_project,  # Use default project for ChatGPT
                 page=1,
-                page_size=10,  # Default pagination
+                page_size=10,
                 context=context,
             )
         )

src/basic_memory/mcp/tools/delete_note.py

@@ -5,7 +5,8 @@ from loguru import logger
 from fastmcp import Context
 from mcp.server.fastmcp.exceptions import ToolError
 
-from basic_memory.mcp.project_context import get_project_client
+from basic_memory.config import ConfigManager
+from basic_memory.mcp.project_context import detect_project_from_url_prefix, get_project_client
 from basic_memory.mcp.server import mcp
 
 
@@ -222,6 +223,16 @@ async def delete_note(
         with suggestions for finding the correct identifier, including search
         commands and alternative formats to try.
     """
+    # Detect project from memory URL prefix before routing
+    # Trigger: identifier starts with memory:// and no explicit project was provided
+    # Why: only gate on memory:// to avoid misrouting plain paths like "research/note"
+    #      where "research" is a directory, not a project name
+    # Outcome: project is set from the URL prefix, routing goes to the correct project
+    if project is None and identifier.strip().startswith("memory://"):
+        detected = detect_project_from_url_prefix(identifier, ConfigManager().config)
+        if detected:
+            project = detected
+
     async with get_project_client(project, workspace, context) as (client, active_project):
         logger.debug(
             f"Deleting {'directory' if is_directory else 'note'}: {identifier} in project: {active_project.name}"
@@ -318,7 +329,7 @@ delete_note("path/to/file.md")
         note_file_path = None
         try:
             # Resolve identifier to entity ID
-            entity_id = await knowledge_client.resolve_entity(identifier)
+            entity_id = await knowledge_client.resolve_entity(identifier, strict=True)
             if output_format == "json":
                 entity = await knowledge_client.get_entity(entity_id)
                 note_title = entity.title

src/basic_memory/mcp/tools/edit_note.py

@@ -5,8 +5,44 @@ from typing import Optional, Literal
 from loguru import logger
 from fastmcp import Context
 
-from basic_memory.mcp.project_context import get_project_client, add_project_metadata
+from basic_memory.config import ConfigManager
+from basic_memory import telemetry
+from basic_memory.mcp.project_context import (
+    detect_project_from_url_prefix,
+    get_project_client,
+    add_project_metadata,
+)
 from basic_memory.mcp.server import mcp
+from basic_memory.schemas.base import Entity
+from basic_memory.schemas.response import EntityResponse
+from basic_memory.utils import validate_project_path
+
+
+def _parse_identifier_to_title_and_directory(identifier: str) -> tuple[str, str]:
+    """Parse an identifier into (title, directory) for creating a new note.
+
+    Strips memory:// prefix if present, then splits on the last '/' to
+    separate the directory path from the note title.
+
+    Examples:
+        "conversations/my-note" → ("my-note", "conversations")
+        "my-note"              → ("my-note", "")
+        "a/b/c/my-note"       → ("my-note", "a/b/c")
+        "memory://a/b/note"   → ("note", "a/b")
+    """
+    cleaned = identifier
+    if cleaned.startswith("memory://"):
+        cleaned = cleaned[len("memory://") :]
+
+    if "/" in cleaned:
+        last_slash = cleaned.rfind("/")
+        directory = cleaned[:last_slash]
+        title = cleaned[last_slash + 1 :]
+    else:
+        directory = ""
+        title = cleaned
+
+    return title, directory
 
 
 def _format_error_response(
@@ -19,15 +55,19 @@ def _format_error_response(
 ) -> str:
     """Format helpful error responses for edit_note failures that guide the AI to retry successfully."""
 
-    # Entity not found errors
+    # Entity not found errors — only reachable for find_replace/replace_section
+    # because append/prepend auto-create the note when it doesn't exist
     if "Entity not found" in error_message or "entity not found" in error_message.lower():
         return f"""# Edit Failed - Note Not Found
 
-The note with identifier '{identifier}' could not be found. Edit operations require an exact match (no fuzzy matching).
+The note with identifier '{identifier}' could not be found. The `find_replace` and `replace_section` operations require an existing note with content to modify.
+
+**Tip:** `append` and `prepend` operations automatically create the note if it doesn't exist.
 
 ## Suggestions to try:
-1. **Search for the note first**: Use `search_notes("{project or "project-name"}", "{identifier.split("/")[-1]}")` to find similar notes with exact identifiers
-2. **Try different exact identifier formats**:
+1. **Use append/prepend instead**: These operations will create the note automatically if it doesn't exist
+2. **Search for the note first**: Use `search_notes("{project or "project-name"}", "{identifier.split("/")[-1]}")` to find similar notes with exact identifiers
+3. **Try different exact identifier formats**:
    - If you used a permalink like "folder/note-title", try the exact title: "{identifier.split("/")[-1].replace("-", " ").title()}"
    - If you used a title, try the exact permalink format: "{identifier.lower().replace(" ", "-")}"
    - Use `read_note("{project or "project-name"}", "{identifier}")` first to verify the note exists and get the exact identifier
@@ -124,7 +164,7 @@ Error editing note '{identifier}': {error_message}
 
 
 @mcp.tool(
-    description="Edit an existing markdown note using various operations like append, prepend, find_replace, or replace_section.",
+    description="Edit an existing markdown note using various operations like append, prepend, find_replace, replace_section, insert_before_section, or insert_after_section.",
     annotations={"destructiveHint": False, "openWorldHint": False},
 )
 async def edit_note(
@@ -135,7 +175,7 @@ async def edit_note(
     workspace: Optional[str] = None,
     section: Optional[str] = None,
     find_text: Optional[str] = None,
-    expected_replacements: int = 1,
+    expected_replacements: Optional[int] = None,
     output_format: Literal["text", "json"] = "text",
     context: Context | None = None,
 ) -> str | dict:
@@ -152,10 +192,12 @@ async def edit_note(
                    Must be an exact match - fuzzy matching is not supported for edit operations.
                    Use search_notes() or read_note() first to find the correct identifier if uncertain.
         operation: The editing operation to perform:
-                  - "append": Add content to the end of the note
-                  - "prepend": Add content to the beginning of the note
-                  - "find_replace": Replace occurrences of find_text with content
-                  - "replace_section": Replace content under a specific markdown header
+                  - "append": Add content to the end of the note (creates the note if it doesn't exist)
+                  - "prepend": Add content to the beginning of the note (creates the note if it doesn't exist)
+                  - "find_replace": Replace occurrences of find_text with content (note must exist)
+                  - "replace_section": Replace content under a specific markdown header (note must exist)
+                  - "insert_before_section": Insert content before a section heading without consuming it (note must exist)
+                  - "insert_after_section": Insert content after a section heading without consuming it (note must exist)
         content: The content to add or use for replacement
         project: Project name to edit in. Optional - server will resolve using hierarchy.
                 If unknown, use list_memory_projects() to discover available projects.
@@ -216,128 +258,256 @@ async def edit_note(
         search_notes() first to find the correct identifier. The tool provides detailed
         error messages with suggestions if operations fail.
     """
-    async with get_project_client(project, workspace, context) as (client, active_project):
-        logger.info("MCP tool call", tool="edit_note", identifier=identifier, operation=operation)
+    # Resolve effective default: allow MCP clients to send null for optional int field
+    effective_replacements = expected_replacements if expected_replacements is not None else 1
 
-        # Validate operation
-        valid_operations = ["append", "prepend", "find_replace", "replace_section"]
-        if operation not in valid_operations:
-            raise ValueError(
-                f"Invalid operation '{operation}'. Must be one of: {', '.join(valid_operations)}"
-            )
+    # Detect project from memory URL prefix before routing
+    # Trigger: identifier starts with memory:// and no explicit project was provided
+    # Why: only gate on memory:// to avoid misrouting plain paths like "research/note"
+    #      where "research" is a directory, not a project name
+    # Outcome: project is set from the URL prefix, routing goes to the correct project
+    if project is None and identifier.strip().startswith("memory://"):
+        detected = detect_project_from_url_prefix(identifier, ConfigManager().config)
+        if detected:
+            project = detected
 
-        # Validate required parameters for specific operations
-        if operation == "find_replace" and not find_text:
-            raise ValueError("find_text parameter is required for find_replace operation")
-        if operation == "replace_section" and not section:
-            raise ValueError("section parameter is required for replace_section operation")
+    with telemetry.operation(
+        "mcp.tool.edit_note",
+        entrypoint="mcp",
+        tool_name="edit_note",
+        requested_project=project,
+        workspace_id=workspace,
+        edit_operation=operation,
+        output_format=output_format,
+        has_section=bool(section),
+        has_find_text=bool(find_text),
+        expected_replacements=effective_replacements,
+    ):
+        async with get_project_client(project, workspace, context) as (client, active_project):
+            with telemetry.contextualize(
+                project_name=active_project.name,
+                workspace_id=workspace,
+                tool_name="edit_note",
+            ):
+                logger.info(
+                    f"MCP tool call tool=edit_note project={active_project.name} "
+                    f"identifier={identifier} operation={operation} output_format={output_format}"
+                )
 
-        # Use the PATCH endpoint to edit the entity
-        try:
-            # Import here to avoid circular import
-            from basic_memory.mcp.clients import KnowledgeClient
+                # Validate operation
+                valid_operations = [
+                    "append",
+                    "prepend",
+                    "find_replace",
+                    "replace_section",
+                    "insert_before_section",
+                    "insert_after_section",
+                ]
+                if operation not in valid_operations:
+                    raise ValueError(
+                        f"Invalid operation '{operation}'. Must be one of: {', '.join(valid_operations)}"
+                    )
 
-            # Use typed KnowledgeClient for API calls
-            knowledge_client = KnowledgeClient(client, active_project.external_id)
+                # Validate required parameters for specific operations
+                if operation == "find_replace" and not find_text:
+                    raise ValueError("find_text parameter is required for find_replace operation")
+                section_ops = ("replace_section", "insert_before_section", "insert_after_section")
+                if operation in section_ops and not section:
+                    raise ValueError("section parameter is required for section-based operations")
 
-            # Resolve identifier to entity ID
-            entity_id = await knowledge_client.resolve_entity(identifier)
+                # Use the PATCH endpoint to edit the entity
+                try:
+                    # Import here to avoid circular import
+                    from basic_memory.mcp.clients import KnowledgeClient
 
-            # Prepare the edit request data
-            edit_data = {
-                "operation": operation,
-                "content": content,
-            }
+                    # Use typed KnowledgeClient for API calls
+                    knowledge_client = KnowledgeClient(client, active_project.external_id)
 
-            # Add optional parameters
-            if section:
-                edit_data["section"] = section
-            if find_text:
-                edit_data["find_text"] = find_text
-            if expected_replacements != 1:  # Only send if different from default
-                edit_data["expected_replacements"] = str(expected_replacements)
+                    file_created = False
+                    entity_id = ""
+                    result: EntityResponse | None = None
 
-            # Call the PATCH endpoint
-            result = await knowledge_client.patch_entity(entity_id, edit_data, fast=False)
+                    # Try to resolve the entity; for append/prepend, create it if not found
+                    try:
+                        entity_id = await knowledge_client.resolve_entity(identifier, strict=True)
+                    except Exception as resolve_error:
+                        # Trigger: entity does not exist yet
+                        # Why: append/prepend can meaningfully create a new note from the content,
+                        #      while find_replace/replace_section require existing content to modify
+                        # Outcome: note is created via the same path as write_note
+                        error_msg = str(resolve_error).lower()
+                        is_not_found = "entity not found" in error_msg or "not found" in error_msg
 
-            # Format summary
-            summary = [
-                f"# Edited note ({operation})",
-                f"project: {active_project.name}",
-                f"file_path: {result.file_path}",
-                f"permalink: {result.permalink}",
-                f"checksum: {result.checksum[:8] if result.checksum else 'unknown'}",
-            ]
+                        if is_not_found and operation in ("append", "prepend"):
+                            title, directory = _parse_identifier_to_title_and_directory(identifier)
 
-            # Add operation-specific details
-            if operation == "append":
-                lines_added = len(content.split("\n"))
-                summary.append(f"operation: Added {lines_added} lines to end of note")
-            elif operation == "prepend":
-                lines_added = len(content.split("\n"))
-                summary.append(f"operation: Added {lines_added} lines to beginning of note")
-            elif operation == "find_replace":
-                # For find_replace, we can't easily count replacements from here
-                # since we don't have the original content, but the server handled it
-                summary.append("operation: Find and replace operation completed")
-            elif operation == "replace_section":
-                summary.append(f"operation: Replaced content under section '{section}'")
+                            # Validate directory path (same security check as write_note)
+                            project_path = active_project.home
+                            if directory and not validate_project_path(directory, project_path):
+                                logger.warning(
+                                    "Attempted path traversal attack blocked",
+                                    directory=directory,
+                                    project=active_project.name,
+                                )
+                                if output_format == "json":
+                                    return {
+                                        "title": title,
+                                        "permalink": None,
+                                        "file_path": None,
+                                        "checksum": None,
+                                        "operation": operation,
+                                        "fileCreated": False,
+                                        "error": "SECURITY_VALIDATION_ERROR",
+                                    }
+                                return f"# Error\n\nDirectory path '{directory}' is not allowed - paths must stay within project boundaries"
 
-            # Count observations by category (reuse logic from write_note)
-            categories = {}
-            if result.observations:
-                for obs in result.observations:
-                    categories[obs.category] = categories.get(obs.category, 0) + 1
+                            entity = Entity(
+                                title=title,
+                                directory=directory,
+                                content_type="text/markdown",
+                                content=content,
+                            )
 
-                summary.append("\n## Observations")
-                for category, count in sorted(categories.items()):
-                    summary.append(f"- {category}: {count}")
+                            logger.info(
+                                "Creating note via edit_note auto-create",
+                                title=title,
+                                directory=directory,
+                                operation=operation,
+                            )
+                            result = await knowledge_client.create_entity(
+                                entity.model_dump(), fast=False
+                            )
+                            file_created = True
+                        else:
+                            # find_replace/replace_section require existing content — re-raise
+                            raise resolve_error
 
-            # Count resolved/unresolved relations
-            unresolved = 0
-            resolved = 0
-            if result.relations:
-                unresolved = sum(1 for r in result.relations if not r.to_id)
-                resolved = len(result.relations) - unresolved
+                    # --- Standard edit path (entity already existed) ---
+                    if not file_created:
+                        # Prepare the edit request data
+                        edit_data = {
+                            "operation": operation,
+                            "content": content,
+                        }
 
-                summary.append("\n## Relations")
-                summary.append(f"- Resolved: {resolved}")
-                if unresolved:
-                    summary.append(f"- Unresolved: {unresolved}")
+                        # Add optional parameters
+                        if section:
+                            edit_data["section"] = section
+                        if find_text:
+                            edit_data["find_text"] = find_text
+                        if effective_replacements != 1:  # Only send if different from default
+                            edit_data["expected_replacements"] = str(effective_replacements)
 
-            logger.info(
-                "MCP tool response",
-                tool="edit_note",
-                operation=operation,
-                project=active_project.name,
-                permalink=result.permalink,
-                observations_count=len(result.observations),
-                relations_count=len(result.relations),
-            )
+                        # Call the PATCH endpoint
+                        result = await knowledge_client.patch_entity(
+                            entity_id, edit_data, fast=False
+                        )
 
-            if output_format == "json":
-                return {
-                    "title": result.title,
-                    "permalink": result.permalink,
-                    "file_path": result.file_path,
-                    "checksum": result.checksum,
-                    "operation": operation,
-                }
+                    # --- Format response ---
+                    # result is always set: either by create_entity (auto-create) or patch_entity (edit)
+                    assert result is not None
+                    if file_created:
+                        summary = [
+                            f"# Created note ({operation})",
+                            f"project: {active_project.name}",
+                            f"file_path: {result.file_path}",
+                            f"permalink: {result.permalink}",
+                            f"checksum: {result.checksum[:8] if result.checksum else 'unknown'}",
+                            "fileCreated: true",
+                        ]
+                        lines_added = len(content.split("\n"))
+                        summary.append(f"operation: Created note with {lines_added} lines")
+                    else:
+                        summary = [
+                            f"# Edited note ({operation})",
+                            f"project: {active_project.name}",
+                            f"file_path: {result.file_path}",
+                            f"permalink: {result.permalink}",
+                            f"checksum: {result.checksum[:8] if result.checksum else 'unknown'}",
+                        ]
 
-            summary_result = "\n".join(summary)
-            return add_project_metadata(summary_result, active_project.name)
+                        # Add operation-specific details
+                        if operation == "append":
+                            lines_added = len(content.split("\n"))
+                            summary.append(f"operation: Added {lines_added} lines to end of note")
+                        elif operation == "prepend":
+                            lines_added = len(content.split("\n"))
+                            summary.append(
+                                f"operation: Added {lines_added} lines to beginning of note"
+                            )
+                        elif operation == "find_replace":
+                            # For find_replace, we can't easily count replacements from here
+                            # since we don't have the original content, but the server handled it
+                            summary.append("operation: Find and replace operation completed")
+                        elif operation == "replace_section":
+                            summary.append(f"operation: Replaced content under section '{section}'")
+                        elif operation == "insert_before_section":
+                            summary.append(
+                                f"operation: Inserted content before section '{section}'"
+                            )
+                        elif operation == "insert_after_section":
+                            summary.append(f"operation: Inserted content after section '{section}'")
 
-        except Exception as e:
-            logger.error(f"Error editing note: {e}")
-            if output_format == "json":
-                return {
-                    "title": None,
-                    "permalink": None,
-                    "file_path": None,
-                    "checksum": None,
-                    "operation": operation,
-                    "error": str(e),
-                }
-            return _format_error_response(
-                str(e), operation, identifier, find_text, expected_replacements, active_project.name
-            )
+                    # Count observations by category (reuse logic from write_note)
+                    categories = {}
+                    if result.observations:
+                        for obs in result.observations:
+                            categories[obs.category] = categories.get(obs.category, 0) + 1
+
+                        summary.append("\n## Observations")
+                        for category, count in sorted(categories.items()):
+                            summary.append(f"- {category}: {count}")
+
+                    # Count resolved/unresolved relations
+                    unresolved = 0
+                    resolved = 0
+                    if result.relations:
+                        unresolved = sum(1 for r in result.relations if not r.to_id)
+                        resolved = len(result.relations) - unresolved
+
+                        summary.append("\n## Relations")
+                        summary.append(f"- Resolved: {resolved}")
+                        if unresolved:
+                            summary.append(f"- Unresolved: {unresolved}")
+
+                    logger.info(
+                        f"MCP tool response: tool=edit_note project={active_project.name} "
+                        f"operation={operation} permalink={result.permalink} "
+                        f"observations_count={len(result.observations)} "
+                        f"relations_count={len(result.relations)} "
+                        f"file_created={str(file_created).lower()}"
+                    )
+
+                    if output_format == "json":
+                        return {
+                            "title": result.title,
+                            "permalink": result.permalink,
+                            "file_path": result.file_path,
+                            "checksum": result.checksum,
+                            "operation": operation,
+                            "fileCreated": file_created,
+                        }
+
+                    summary_result = "\n".join(summary)
+                    return add_project_metadata(summary_result, active_project.name)
+
+                except Exception as e:
+                    logger.error(f"Error editing note: {e}")
+                    if output_format == "json":
+                        return {
+                            "title": None,
+                            "permalink": None,
+                            "file_path": None,
+                            "checksum": None,
+                            "operation": operation,
+                            "fileCreated": False,
+                            "error": str(e),
+                        }
+                    return _format_error_response(
+                        str(e),
+                        operation,
+                        identifier,
+                        find_text,
+                        effective_replacements,
+                        active_project.name,
+                    )

src/basic_memory/mcp/tools/move_note.py

@@ -6,6 +6,7 @@ from typing import Optional, Literal
 
 from loguru import logger
 from fastmcp import Context
+from mcp.server.fastmcp.exceptions import ToolError
 
 from basic_memory.mcp.server import mcp
 from basic_memory.mcp.project_context import get_project_client
@@ -476,8 +477,11 @@ async def move_note(
             }
         return f"# Move Failed - Invalid Parameters\n\n{error_msg}"
     async with get_project_client(project, workspace, context) as (client, active_project):
-        logger.debug(
-            f"Moving {'directory' if is_directory else 'note'}: {identifier} to {destination_path} in project: {active_project.name}"
+        destination_target = destination_folder or destination_path
+        logger.info(
+            f"MCP tool call tool=move_note project={active_project.name} "
+            f"identifier={identifier} destination={destination_target} "
+            f"is_directory={str(is_directory).lower()}"
         )
 
         # Validate destination path to prevent path traversal attacks
@@ -637,7 +641,7 @@ move_note("path/to/file.md", "{destination_path}/file.md")
             """Resolve and cache the source entity ID for the duration of this move."""
             nonlocal resolved_entity_id
             if resolved_entity_id is None:
-                resolved_entity_id = await knowledge_client.resolve_entity(identifier)
+                resolved_entity_id = await knowledge_client.resolve_entity(identifier, strict=True)
             return resolved_entity_id
 
         try:
@@ -645,8 +649,26 @@ move_note("path/to/file.md", "{destination_path}/file.md")
             source_entity = await knowledge_client.get_entity(resolved_entity_id)
             if "." in source_entity.file_path:
                 source_ext = source_entity.file_path.split(".")[-1]
+        except ToolError as e:
+            # Trigger: strict=True resolve_entity raised because the entity was not found.
+            # Why: fail fast with a formatted error instead of silently falling through
+            #      to extension defaults and failing later with a confusing message.
+            # Outcome: move_note returns a user-facing not-found error immediately.
+            logger.error(f"Move failed for '{identifier}' to '{destination_path}': {e}")
+            if output_format == "json":
+                return {
+                    "moved": False,
+                    "title": None,
+                    "permalink": None,
+                    "file_path": None,
+                    "source": identifier,
+                    "destination": destination_path,
+                    "error": str(e),
+                }
+            return _format_move_error_response(str(e), identifier, destination_path)
         except Exception as e:
-            # If we can't fetch source metadata, continue with extension defaults.
+            # If we can't fetch source metadata (e.g. get_entity or file_path parsing fails),
+            # continue with extension defaults — the entity was at least resolved.
             logger.debug(f"Could not fetch source entity for extension check: {e}")
 
         # --- Resolve destination_folder into destination_path ---
@@ -815,10 +837,8 @@ move_note("{identifier}", destination_folder="notes")
 
             # Log the operation
             logger.info(
-                "Move note completed",
-                identifier=identifier,
-                destination_path=destination_path,
-                project=active_project.name,
+                f"MCP tool response: tool=move_note project={active_project.name} "
+                f"source={identifier} destination={result.file_path} permalink={result.permalink}"
             )
 
             return "\n".join(result_lines)

src/basic_memory/mcp/tools/read_content.py

@@ -216,7 +216,7 @@ async def read_content(
         if detected:
             project = detected
 
-    logger.info("Reading file", path=path, project=project)
+    logger.info(f"MCP tool call tool=read_content project={project} path={path}")
 
     async with get_project_client(project, workspace, context) as (client, active_project):
         # Resolve path with project-prefix awareness for memory:// URLs
@@ -260,6 +260,10 @@ async def read_content(
         # Handle text or json
         if content_type.startswith("text/") or content_type == "application/json":
             logger.debug("Processing text resource")
+            logger.info(
+                f"MCP tool response: tool=read_content project={active_project.name} "
+                f"path={url} type=text content_type={content_type}"
+            )
             return {
                 "type": "text",
                 "text": response.text,
@@ -272,6 +276,10 @@ async def read_content(
             logger.debug("Processing image")
             img = PILImage.open(io.BytesIO(response.content))
             img_bytes = optimize_image(img, content_length)
+            logger.info(
+                f"MCP tool response: tool=read_content project={active_project.name} "
+                f"path={url} type=image content_type=image/jpeg"
+            )
 
             return {
                 "type": "image",
@@ -291,6 +299,10 @@ async def read_content(
                     "type": "error",
                     "error": f"Document size {content_length} bytes exceeds maximum allowed size",
                 }
+            logger.info(
+                f"MCP tool response: tool=read_content project={active_project.name} "
+                f"path={url} type=document content_type={content_type}"
+            )
             return {
                 "type": "document",
                 "source": {

src/basic_memory/mcp/tools/read_note.py

@@ -8,6 +8,7 @@ import yaml
 from loguru import logger
 from fastmcp import Context
 
+from basic_memory import telemetry
 from basic_memory.config import ConfigManager
 from basic_memory.mcp.project_context import (
     detect_project_from_url_prefix,
@@ -139,186 +140,224 @@ async def read_note(
         if detected:
             project = detected
 
-    async with get_project_client(project, workspace, context) as (client, active_project):
-        # Resolve identifier with project-prefix awareness for memory:// URLs
-        _, entity_path, _ = await resolve_project_and_path(client, identifier, project, context)
+    with telemetry.operation(
+        "mcp.tool.read_note",
+        entrypoint="mcp",
+        tool_name="read_note",
+        requested_project=project,
+        workspace_id=workspace,
+        output_format=output_format,
+        page=page,
+        page_size=page_size,
+        include_frontmatter=include_frontmatter,
+    ):
+        async with get_project_client(project, workspace, context) as (client, active_project):
+            with telemetry.contextualize(
+                project_name=active_project.name,
+                workspace_id=workspace,
+                tool_name="read_note",
+            ):
+                # Resolve identifier with project-prefix awareness for memory:// URLs
+                _, entity_path, _ = await resolve_project_and_path(
+                    client, identifier, project, context
+                )
 
-        # Validate identifier to prevent path traversal attacks
-        # For memory:// URLs, validate the extracted path (not the raw URL which
-        # has a scheme prefix that confuses path validation)
-        raw_path = memory_url_path(identifier) if identifier.startswith("memory://") else identifier
-        processed_path = entity_path
-        project_path = active_project.home
+                # Validate identifier to prevent path traversal attacks
+                # For memory:// URLs, validate the extracted path (not the raw URL which
+                # has a scheme prefix that confuses path validation)
+                raw_path = (
+                    memory_url_path(identifier)
+                    if identifier.startswith("memory://")
+                    else identifier
+                )
+                processed_path = entity_path
+                project_path = active_project.home
 
-        if not validate_project_path(raw_path, project_path) or not validate_project_path(
-            processed_path, project_path
-        ):
-            logger.warning(
-                "Attempted path traversal attack blocked",
-                identifier=identifier,
-                processed_path=processed_path,
-                project=active_project.name,
-            )
-            if output_format == "json":
-                return {
-                    "title": None,
-                    "permalink": None,
-                    "file_path": None,
-                    "content": None,
-                    "frontmatter": None,
-                    "error": "SECURITY_VALIDATION_ERROR",
-                }
-            return f"# Error\n\nIdentifier '{identifier}' is not allowed - paths must stay within project boundaries"
-
-        # Get the file via REST API - first try direct identifier resolution
-        logger.info(
-            f"Attempting to read note from Project: {active_project.name} identifier: {entity_path}"
-        )
-
-        # Import here to avoid circular import
-        from basic_memory.mcp.clients import KnowledgeClient, ResourceClient
-
-        # Use typed clients for API calls
-        knowledge_client = KnowledgeClient(client, active_project.external_id)
-        resource_client = ResourceClient(client, active_project.external_id)
-
-        async def _read_json_payload(entity_id: str) -> dict:
-            entity = await knowledge_client.get_entity(entity_id)
-            response = await resource_client.read(entity_id, page=page, page_size=page_size)
-            content_text = response.text
-            body_content, parsed_frontmatter = _parse_opening_frontmatter(content_text)
-            return {
-                "title": entity.title,
-                "permalink": entity.permalink,
-                "file_path": entity.file_path,
-                "content": content_text if include_frontmatter else body_content,
-                "frontmatter": parsed_frontmatter,
-            }
-
-        def _empty_json_payload() -> dict:
-            return {
-                "title": None,
-                "permalink": None,
-                "file_path": None,
-                "content": None,
-                "frontmatter": None,
-            }
-
-        def _search_results(payload: object) -> list[dict]:
-            if not isinstance(payload, dict):
-                return []
-            results = payload.get("results")
-            return results if isinstance(results, list) else []
-
-        def _result_title(item: dict) -> str:
-            return str(item.get("title") or "")
-
-        def _result_permalink(item: dict) -> Optional[str]:
-            value = item.get("permalink")
-            return str(value) if value else None
-
-        def _result_file_path(item: dict) -> Optional[str]:
-            value = item.get("file_path")
-            return str(value) if value else None
-
-        try:
-            # Try to resolve identifier to entity ID
-            entity_id = await knowledge_client.resolve_entity(entity_path, strict=True)
-
-            # Fetch content using entity ID
-            response = await resource_client.read(entity_id, page=page, page_size=page_size)
-
-            # If successful, return the content
-            if response.status_code == 200:
-                logger.info("Returning read_note result from resource: {path}", path=entity_path)
-                if output_format == "json":
-                    return await _read_json_payload(entity_id)
-                return response.text
-        except Exception as e:  # pragma: no cover
-            logger.info(f"Direct lookup failed for '{entity_path}': {e}")
-            # Continue to fallback methods
-
-        # Fallback 1: Try title search via API
-        logger.info(f"Search title for: {identifier}")
-        title_results = await search_notes(
-            query=identifier,
-            search_type="title",
-            project=active_project.name,
-            workspace=workspace,
-            output_format="json",
-            context=context,
-        )
-
-        title_candidates = _search_results(title_results)
-        if title_candidates:
-            # Trigger: direct resolution failed and title search returned candidates.
-            # Why: avoid returning unrelated notes when search yields only fuzzy matches.
-            # Outcome: fetch content only when a true exact title match exists.
-            result = next(
-                (
-                    candidate
-                    for candidate in title_candidates
-                    if _is_exact_title_match(identifier, _result_title(candidate))
-                ),
-                None,
-            )
-            if not result:
-                logger.info(f"No exact title match found for: {identifier}")
-            elif _result_permalink(result):
-                try:
-                    # Resolve the permalink to entity ID
-                    entity_id = await knowledge_client.resolve_entity(
-                        _result_permalink(result) or "", strict=True
+                if not validate_project_path(raw_path, project_path) or not validate_project_path(
+                    processed_path, project_path
+                ):
+                    logger.warning(
+                        "Attempted path traversal attack blocked",
+                        identifier=identifier,
+                        processed_path=processed_path,
+                        project=active_project.name,
                     )
+                    if output_format == "json":
+                        return {
+                            "title": None,
+                            "permalink": None,
+                            "file_path": None,
+                            "content": None,
+                            "frontmatter": None,
+                            "error": "SECURITY_VALIDATION_ERROR",
+                        }
+                    return f"# Error\n\nIdentifier '{identifier}' is not allowed - paths must stay within project boundaries"
 
-                    # Fetch content using the entity ID
+                # Get the file via REST API - first try direct identifier resolution
+                logger.info(
+                    f"Attempting to read note from Project: {active_project.name} identifier: {entity_path}"
+                )
+
+                # Import here to avoid circular import
+                from basic_memory.mcp.clients import KnowledgeClient, ResourceClient
+
+                # Use typed clients for API calls
+                knowledge_client = KnowledgeClient(client, active_project.external_id)
+                resource_client = ResourceClient(client, active_project.external_id)
+
+                async def _read_json_payload(entity_id: str) -> dict:
+                    with telemetry.scope(
+                        "mcp.read_note.shape_response",
+                        domain="mcp",
+                        action="read_note",
+                        phase="shape_response",
+                    ):
+                        entity = await knowledge_client.get_entity(entity_id)
+                        response = await resource_client.read(
+                            entity_id, page=page, page_size=page_size
+                        )
+                        content_text = response.text
+                        body_content, parsed_frontmatter = _parse_opening_frontmatter(content_text)
+                        return {
+                            "title": entity.title,
+                            "permalink": entity.permalink,
+                            "file_path": entity.file_path,
+                            "content": content_text if include_frontmatter else body_content,
+                            "frontmatter": parsed_frontmatter,
+                        }
+
+                def _empty_json_payload() -> dict:
+                    return {
+                        "title": None,
+                        "permalink": None,
+                        "file_path": None,
+                        "content": None,
+                        "frontmatter": None,
+                    }
+
+                def _search_results(payload: object) -> list[dict]:
+                    if not isinstance(payload, dict):
+                        return []
+                    results = payload.get("results")
+                    return results if isinstance(results, list) else []
+
+                async def _search_candidates(identifier_text: str, *, title_only: bool) -> dict:
+                    # Trigger: direct entity resolution failed for the caller's identifier.
+                    # Why: search_notes applies the same memory:// normalization and tool-level
+                    #      query handling as the rest of MCP routing, which raw client calls skip.
+                    # Outcome: unresolved memory URLs still fall back through normalized search.
+                    search_type = "title" if title_only else "text"
+                    response = await search_notes(
+                        project=active_project.name,
+                        workspace=workspace,
+                        query=identifier_text,
+                        search_type=search_type,
+                        page=page,
+                        page_size=page_size,
+                        output_format="json",
+                        context=context,
+                    )
+                    return response if isinstance(response, dict) else {}
+
+                def _result_title(item: dict) -> str:
+                    return str(item.get("title") or "")
+
+                def _result_permalink(item: dict) -> Optional[str]:
+                    value = item.get("permalink")
+                    return str(value) if value else None
+
+                def _result_file_path(item: dict) -> Optional[str]:
+                    value = item.get("file_path")
+                    return str(value) if value else None
+
+                try:
+                    # Try to resolve identifier to entity ID
+                    entity_id = await knowledge_client.resolve_entity(entity_path, strict=True)
+
+                    # Fetch content using entity ID
                     response = await resource_client.read(entity_id, page=page, page_size=page_size)
 
+                    # If successful, return the content
                     if response.status_code == 200:
                         logger.info(
-                            f"Found note by exact title search: {_result_permalink(result)}"
+                            "Returning read_note result from resource: {path}", path=entity_path
                         )
                         if output_format == "json":
                             return await _read_json_payload(entity_id)
                         return response.text
                 except Exception as e:  # pragma: no cover
-                    logger.info(
-                        f"Failed to fetch content for found title match {_result_permalink(result)}: {e}"
+                    logger.info(f"Direct lookup failed for '{entity_path}': {e}")
+                    # Continue to fallback methods
+
+                # Fallback 1: Try title search via API
+                logger.info(f"Search title for: {identifier}")
+                title_results = await _search_candidates(identifier, title_only=True)
+
+                title_candidates = _search_results(title_results)
+                if title_candidates:
+                    # Trigger: direct resolution failed and title search returned candidates.
+                    # Why: avoid returning unrelated notes when search yields only fuzzy matches.
+                    # Outcome: fetch content only when a true exact title match exists.
+                    result = next(
+                        (
+                            candidate
+                            for candidate in title_candidates
+                            if _is_exact_title_match(identifier, _result_title(candidate))
+                        ),
+                        None,
                     )
-        else:
-            logger.info(
-                f"No results in title search for: {identifier} in project {active_project.name}"
-            )
+                    if not result:
+                        logger.info(f"No exact title match found for: {identifier}")
+                    elif _result_permalink(result):
+                        try:
+                            # Resolve the permalink to entity ID
+                            entity_id = await knowledge_client.resolve_entity(
+                                _result_permalink(result) or "", strict=True
+                            )
 
-        # Fallback 2: Text search as a last resort
-        logger.info(f"Title search failed, trying text search for: {identifier}")
-        text_results = await search_notes(
-            query=identifier,
-            search_type="text",
-            project=active_project.name,
-            workspace=workspace,
-            output_format="json",
-            context=context,
-        )
+                            # Fetch content using the entity ID
+                            response = await resource_client.read(
+                                entity_id, page=page, page_size=page_size
+                            )
 
-        # We didn't find a direct match, construct a helpful error message
-        text_candidates = _search_results(text_results)
-        if not text_candidates:
-            if output_format == "json":
-                return _empty_json_payload()
-            return format_not_found_message(active_project.name, identifier)
-        if output_format == "json":
-            payload = _empty_json_payload()
-            payload["related_results"] = [
-                {
-                    "title": _result_title(result),
-                    "permalink": _result_permalink(result),
-                    "file_path": _result_file_path(result),
-                }
-                for result in text_candidates[:5]
-            ]
-            return payload
-        return format_related_results(active_project.name, identifier, text_candidates[:5])
+                            if response.status_code == 200:
+                                logger.info(
+                                    f"Found note by exact title search: {_result_permalink(result)}"
+                                )
+                                if output_format == "json":
+                                    return await _read_json_payload(entity_id)
+                                return response.text
+                        except Exception as e:  # pragma: no cover
+                            logger.info(
+                                f"Failed to fetch content for found title match {_result_permalink(result)}: {e}"
+                            )
+                else:
+                    logger.info(
+                        f"No results in title search for: {identifier} in project {active_project.name}"
+                    )
+
+                # Fallback 2: Text search as a last resort
+                logger.info(f"Title search failed, trying text search for: {identifier}")
+                text_results = await _search_candidates(identifier, title_only=False)
+
+                # We didn't find a direct match, construct a helpful error message
+                text_candidates = _search_results(text_results)
+                if not text_candidates:
+                    if output_format == "json":
+                        return _empty_json_payload()
+                    return format_not_found_message(active_project.name, identifier)
+                if output_format == "json":
+                    payload = _empty_json_payload()
+                    payload["related_results"] = [
+                        {
+                            "title": _result_title(result),
+                            "permalink": _result_permalink(result),
+                            "file_path": _result_file_path(result),
+                        }
+                        for result in text_candidates[:5]
+                    ]
+                    return payload
+                return format_related_results(active_project.name, identifier, text_candidates[:5])
 
 
 def format_not_found_message(project: str | None, identifier: str) -> str:

src/basic_memory/mcp/tools/schema.py

@@ -11,7 +11,141 @@ from fastmcp import Context
 
 from basic_memory.mcp.project_context import get_project_client
 from basic_memory.mcp.server import mcp
-from basic_memory.schemas.schema import ValidationReport, InferenceReport, DriftReport
+from basic_memory.schemas.schema import DriftReport, InferenceReport, ValidationReport
+
+
+def _format_validation_report(report: ValidationReport) -> str:
+    """Render a ValidationReport as readable markdown.
+
+    Produces output the LLM can display directly instead of trying to
+    interpret raw JSON, which leads to "undefined — invalid" rendering.
+    """
+    lines: list[str] = []
+
+    # --- Header ---
+    type_label = report.note_type or "all"
+    lines.append(f"# Schema Validation: {type_label}")
+    lines.append("")
+    lines.append(
+        f"Notes: {report.total_notes} | Valid: {report.valid_count} "
+        f"| Warnings: {report.warning_count} | Errors: {report.error_count}"
+    )
+    lines.append("")
+
+    # --- Per-note results ---
+    for r in report.results:
+        status = "valid" if r.passed else "INVALID"
+        lines.append(f"- **{r.note_identifier}** — {status}")
+        for w in r.warnings:
+            lines.append(f"  - warning: {w}")
+        for e in r.errors:
+            lines.append(f"  - error: {e}")
+
+    return "\n".join(lines)
+
+
+def _format_inference_report(report: InferenceReport) -> str:
+    """Render an InferenceReport as readable markdown.
+
+    Without this formatter the LLM receives raw JSON and renders
+    field names as "undefined".
+    """
+    lines: list[str] = []
+
+    # --- Header ---
+    lines.append(f"# Schema Inference: {report.note_type}")
+    lines.append("")
+    lines.append(f"Notes analyzed: {report.notes_analyzed}")
+    lines.append("")
+
+    # --- Suggested schema YAML ---
+    if report.suggested_schema:
+        lines.append("## Suggested Schema")
+        lines.append("")
+        lines.append("```yaml")
+        lines.append("---")
+        lines.append(f"title: {report.note_type.title()}")
+        lines.append("type: schema")
+        lines.append(f"entity: {report.note_type}")
+        lines.append("version: 1")
+        lines.append("schema:")
+        for field_name, field_def in report.suggested_schema.items():
+            lines.append(f"  {field_name}: {field_def}")
+        lines.append("---")
+        lines.append("```")
+        lines.append("")
+
+    # --- Field frequency table ---
+    if report.field_frequencies:
+        lines.append("## Field Frequencies")
+        lines.append("")
+        for f in report.field_frequencies:
+            pct = f"{f.percentage:.0%}"
+            req_marker = "required" if f.name in report.suggested_required else "optional"
+            samples = ", ".join(f.sample_values[:3]) if f.sample_values else ""
+            sample_str = f" (e.g. {samples})" if samples else ""
+            lines.append(
+                f"- **{f.name}** ({f.source}) — {pct} ({f.count}/{f.total}) "
+                f"[{req_marker}]{sample_str}"
+            )
+        lines.append("")
+
+    # --- Excluded fields ---
+    if report.excluded:
+        lines.append("## Excluded (below threshold)")
+        lines.append("")
+        for name in report.excluded:
+            lines.append(f"- {name}")
+        lines.append("")
+
+    return "\n".join(lines)
+
+
+def _format_drift_report(report: DriftReport) -> str:
+    """Render a DriftReport as readable markdown.
+
+    Without this formatter the LLM receives raw JSON and renders
+    field names as "undefined".
+    """
+    lines: list[str] = []
+
+    # --- Header ---
+    lines.append(f"# Schema Drift: {report.note_type}")
+    lines.append("")
+
+    has_drift = report.new_fields or report.dropped_fields or report.cardinality_changes
+
+    if not has_drift:
+        lines.append("No drift detected — schema matches actual usage.")
+        return "\n".join(lines)
+
+    # --- New fields ---
+    if report.new_fields:
+        lines.append("## New Fields (in notes but not in schema)")
+        lines.append("")
+        for f in report.new_fields:
+            pct = f"{f.percentage:.0%}"
+            lines.append(f"- **{f.name}** ({f.source}) — {pct} ({f.count}/{f.total})")
+        lines.append("")
+
+    # --- Dropped fields ---
+    if report.dropped_fields:
+        lines.append("## Dropped Fields (in schema but rare in notes)")
+        lines.append("")
+        for f in report.dropped_fields:
+            pct = f"{f.percentage:.0%}"
+            lines.append(f"- **{f.name}** ({f.source}) — {pct} ({f.count}/{f.total})")
+        lines.append("")
+
+    # --- Cardinality changes ---
+    if report.cardinality_changes:
+        lines.append("## Cardinality Changes")
+        lines.append("")
+        for change in report.cardinality_changes:
+            lines.append(f"- {change}")
+        lines.append("")
+
+    return "\n".join(lines)
 
 
 def _no_notes_guidance(note_type: str, tool_name: str) -> str:
@@ -26,7 +160,7 @@ def _no_notes_guidance(note_type: str, tool_name: str) -> str:
         f"## Next Steps\n\n"
         f"1. **Create notes of this type** — use `write_note` with "
         f'`note_type="{note_type}"` to create notes\n'
-        f"2. **Check existing types** — use `search_notes` with `entity_types` "
+        f"2. **Check existing types** — use `search_notes` with `note_types` "
         f"filter to see what types exist\n"
         f"3. **Browse content** — use `list_directory` or `recent_activity` to "
         f"see what's in the project\n"
@@ -142,24 +276,25 @@ async def schema_validate(
             # Trigger: no entities of this type exist in the project
             # Why: can't validate notes that don't exist yet
             # Outcome: return guidance on creating notes of this type
-            if note_type and result.total_entities == 0:
+            effective_type = note_type or result.note_type or "unknown"
+            if result.total_entities == 0:
                 if output_format == "json":
-                    return {"error": f"No notes found of type '{note_type}'"}
-                return _no_notes_guidance(note_type, "schema_validate")
+                    return {"error": f"No notes found of type '{effective_type}'"}
+                return _no_notes_guidance(effective_type, "schema_validate")
 
             # --- No schema guard ---
             # Trigger: entities exist but none were validated (no schema found)
             # Why: notes of this type exist but no schema was found, so none were validated
             # Outcome: return guidance on how to create a schema
-            if note_type and result.total_notes == 0:
+            if result.total_notes == 0:
                 if output_format == "json":
-                    return {"error": f"No schema found for type '{note_type}'"}
-                return _no_schema_guidance(note_type, "schema_validate")
+                    return {"error": f"No schema found for type '{effective_type}'"}
+                return _no_schema_guidance(effective_type, "schema_validate")
 
             if output_format == "json":
                 return result.model_dump(mode="json", exclude_none=True)
 
-            return result
+            return _format_validation_report(result)
 
         except Exception as e:
             logger.error(f"Schema validation failed: {e}, project: {active_project.name}")
@@ -186,7 +321,7 @@ async def schema_infer(
     workspace: Optional[str] = None,
     output_format: Literal["text", "json"] = "text",
     context: Context | None = None,
-) -> InferenceReport | str | dict:
+) -> str | dict:
     """Analyze existing notes and suggest a schema definition.
 
     Examines observation categories and relation types across all notes
@@ -262,7 +397,7 @@ async def schema_infer(
                     f"share a consistent structure.\n\n"
                     f"## Suggestions\n"
                     f"1. **Use a more specific type** — try `search_notes` with "
-                    f"`entity_types` filter to see what types exist\n"
+                    f"`note_types` filter to see what types exist\n"
                     f"2. **Lower the threshold** — "
                     f'`schema_infer("{note_type}", threshold=0.1)` to include '
                     f"rarer fields\n"
@@ -274,7 +409,7 @@ async def schema_infer(
             if output_format == "json":
                 return result.model_dump(mode="json", exclude_none=True)
 
-            return result
+            return _format_inference_report(result)
 
         except Exception as e:
             logger.error(f"Schema inference failed: {e}, project: {active_project.name}")
@@ -300,7 +435,7 @@ async def schema_diff(
     workspace: Optional[str] = None,
     output_format: Literal["text", "json"] = "text",
     context: Context | None = None,
-) -> DriftReport | str | dict:
+) -> str | dict:
     """Detect drift between a schema definition and actual note usage.
 
     Compares the existing schema for a note type against how notes of
@@ -362,7 +497,7 @@ async def schema_diff(
             if output_format == "json":
                 return result.model_dump(mode="json", exclude_none=True)
 
-            return result
+            return _format_drift_report(result)
 
         except Exception as e:
             logger.error(f"Schema diff failed: {e}, project: {active_project.name}")

src/basic_memory/mcp/tools/search.py

@@ -1,12 +1,16 @@
 """Search tools for Basic Memory MCP server."""
 
+import re
 from textwrap import dedent
-from typing import List, Optional, Dict, Any, Literal
+from typing import Annotated, List, Optional, Dict, Any, Literal
 
 from loguru import logger
 from fastmcp import Context
+from pydantic import BeforeValidator
 
+from basic_memory import telemetry
 from basic_memory.config import ConfigManager
+from basic_memory.utils import coerce_dict, coerce_list
 from basic_memory.mcp.container import get_container
 from basic_memory.mcp.project_context import (
     detect_project_from_url_prefix,
@@ -22,20 +26,20 @@ from basic_memory.schemas.search import (
 )
 
 
-def _semantic_search_enabled_for_text_search() -> bool:
-    """Resolve semantic-search enablement in both MCP and CLI invocation paths."""
-    try:
-        return get_container().config.semantic_search_enabled
-    except RuntimeError:
-        # Trigger: MCP container is not initialized (e.g., `bm tool search-notes` direct call).
-        # Why: CLI path still needs the same semantic-default behavior as MCP server path.
-        # Outcome: load config directly and keep text-mode retrieval behavior consistent.
-        return ConfigManager().config.semantic_search_enabled
-
-
 def _default_search_type() -> str:
-    """Pick default search mode from semantic-search config."""
-    return "hybrid" if _semantic_search_enabled_for_text_search() else "text"
+    """Pick default search mode from config, falling back to auto-detection.
+
+    Priority: config default_search_type > auto-detect (hybrid if semantic enabled, else text).
+    """
+    try:
+        config = get_container().config
+    except RuntimeError:
+        config = ConfigManager().config
+
+    if config.default_search_type:
+        return config.default_search_type
+
+    return "hybrid" if config.semantic_search_enabled else "text"
 
 
 def _format_search_error_response(
@@ -164,7 +168,7 @@ def _format_search_error_response(
                - Remove restrictive terms: Focus on the most important keywords
 
             5. **Use filtering to narrow scope**:
-               - By content type: `search_notes("{project}","{query}", note_types=["note"])`
+               - By note type in frontmatter: `search_notes("{project}","{query}", note_types=["note"])`
                - By recent content: `search_notes("{project}","{query}", after_date="1 week")`
                - By entity type: `search_notes("{project}","{query}", entity_types=["observation"])`
 
@@ -250,6 +254,46 @@ Error searching for '{query}': {error_message}
 - **Patterns**: `tag:example`, `category:observation`"""
 
 
+def _format_search_markdown(result: SearchResponse, project: str, query: str | None) -> str:
+    """Format SearchResponse as compact markdown text.
+
+    Produces a human-readable markdown representation suitable for LLM
+    consumption when structured data isn't needed.
+    """
+    if not result.results:
+        return f"No results found for '{query or ''}' in project '{project}'."
+
+    parts = []
+
+    # --- Header ---
+    if query:
+        parts.append(f"# Search Results: {query}")
+    else:
+        parts.append("# Search Results")
+    parts.append(f"*project: {project}*")
+    parts.append("")
+
+    # --- Result blocks ---
+    for r in result.results:
+        parts.append(f"### {r.title}")
+        parts.append(f"- permalink: {r.permalink}")
+        parts.append(f"- score: {r.score:.4f}")
+        if r.matched_chunk:
+            parts.append(f"- match: {r.matched_chunk[:200]}")
+        parts.append("")
+
+    # --- Footer with pagination ---
+    parts.append("---")
+    count = len(result.results)
+    parts.append(
+        f"*{count} result{'s' if count != 1 else ''}"
+        f" | page {result.current_page}, page_size {result.page_size}"
+        f"{' | more available' if result.has_more else ''}*"
+    )
+
+    return "\n".join(parts)
+
+
 @mcp.tool(
     description="Search across all content in the knowledge base with advanced syntax support.",
     # TODO: re-enable once MCP client rendering is working
@@ -257,22 +301,39 @@ Error searching for '{query}': {error_message}
     annotations={"readOnlyHint": True, "openWorldHint": False},
 )
 async def search_notes(
-    query: str,
+    query: Optional[str] = None,
     project: Optional[str] = None,
     workspace: Optional[str] = None,
     page: int = 1,
     page_size: int = 10,
     search_type: str | None = None,
     output_format: Literal["text", "json"] = "text",
-    note_types: List[str] | None = None,
-    entity_types: List[str] | None = None,
+    note_types: Annotated[
+        List[str] | None,
+        BeforeValidator(coerce_list),
+        "Filter by the 'type' field in note frontmatter (e.g. 'note', 'chapter', 'person'). "
+        "Case-insensitive.",
+    ] = None,
+    entity_types: Annotated[
+        List[str] | None,
+        BeforeValidator(coerce_list),
+        "Filter by knowledge graph item type: 'entity' (whole notes), 'observation', or "
+        "'relation'. Defaults to 'entity'. Do NOT pass schema/frontmatter types like "
+        "'Chapter' here — use note_types instead.",
+    ] = None,
     after_date: Optional[str] = None,
-    metadata_filters: Optional[Dict[str, Any]] = None,
-    tags: Optional[List[str]] = None,
+    metadata_filters: Annotated[
+        Dict[str, Any] | None,
+        BeforeValidator(coerce_dict),
+    ] = None,
+    tags: Annotated[
+        List[str] | None,
+        BeforeValidator(coerce_list),
+    ] = None,
     status: Optional[str] = None,
     min_similarity: Optional[float] = None,
     context: Context | None = None,
-) -> SearchResponse | dict | str:
+) -> dict | str:
     """Search across all content in the knowledge base with comprehensive syntax support.
 
     This tool searches the knowledge base using full-text search, pattern matching,
@@ -302,13 +363,14 @@ async def search_notes(
     - `search_notes("work-project", "category:observation")` - Filter by observation categories
     - `search_notes("team-docs", "author:username")` - Find content by author (if metadata available)
 
-    **Note:** `tag:` shorthand requires `search_type="text"` when semantic search is enabled
-    (the default is hybrid). Alternatively, use the `tags` parameter for tag filtering with
-    any search type: `search_notes("project", "query", tags=["my-tag"])`
+    **Note:** `tag:` shorthand is automatically converted to a `tags` filter, so it works
+    with any search type (text, hybrid, vector). You can also use the `tags` parameter
+    directly: `search_notes("project", "query", tags=["my-tag"])`
 
     ### Search Type Examples
     - `search_notes("my-project", "Meeting", search_type="title")` - Search only in titles
     - `search_notes("work-docs", "docs/meeting-*", search_type="permalink")` - Pattern match permalinks
+      Note: Permalink patterns match the full path (e.g., "project/folder/chapter-13*", not just "chapter-13*").
     - `search_notes("research", "keyword")` - Default search (hybrid when semantic is enabled,
       text when disabled)
 
@@ -333,8 +395,10 @@ async def search_notes(
     - Nested keys use dot notation (e.g., `"schema.confidence"`).
 
     ### Filter-only Searches
-    You can pass an empty query string when only using structured filters:
-    - `search_notes("my-project", "", metadata_filters={"type": "spec"})`
+    Omit `query` (or pass None) when only using structured filters:
+    - `search_notes(metadata_filters={"type": "spec"}, project="my-project")`
+    - `search_notes(tags=["security"], project="my-project")`
+    - `search_notes(status="draft", project="my-project")`
 
     ### Convenience Filters
     `tags` and `status` are shorthand for metadata_filters. If the same key exists in
@@ -347,7 +411,8 @@ async def search_notes(
     - `search_notes("archive", "docs/2024-*", search_type="permalink")` - Year-based permalink search
 
     Args:
-        query: The search query string (supports boolean operators, phrases, patterns)
+        query: Optional search query string (supports boolean operators, phrases, patterns).
+              Omit or pass None for filter-only searches using metadata_filters, tags, or status.
         project: Project name to search in. Optional - server will resolve using hierarchy.
                 If unknown, use list_memory_projects() to discover available projects.
         page: The page number of results to return (default 1)
@@ -369,7 +434,8 @@ async def search_notes(
         context: Optional FastMCP context for performance caching.
 
     Returns:
-        SearchResponse with results and pagination info, or helpful error guidance if search fails
+        Formatted markdown text (output_format="text"), dict (output_format="json"),
+        or helpful error guidance string if search fails
 
     Examples:
         # Basic text search
@@ -391,7 +457,7 @@ async def search_notes(
         # Exact phrase search
         results = await search_notes("\"weekly standup meeting\"")
 
-        # Search with note type filter
+        # Search with note type filter - type property in frontmatter
         results = await search_notes(
             "meeting notes",
             note_types=["note"],
@@ -432,176 +498,185 @@ async def search_notes(
         results = await search_notes("project planning", project="my-project")
     """
     # Avoid mutable-default-argument footguns. Treat None as "no filter".
-    note_types = note_types or []
+    # Lowercase note_types so "Chapter" matches the stored "chapter".
+    note_types = [t.lower() for t in note_types] if note_types else []
     entity_types = entity_types or []
 
+    # Parse tag:<value> shorthand at tool level so it works with all search modes.
+    # Handles "tag:security", "tag:coffee tag:brewing", "tag:coffee AND tag:brewing".
+    # Without this, hybrid/vector modes fail because they require non-empty text,
+    # but the service-layer tag: parser clears the text after the mode is set.
+    if query and "tag:" in query.lower():
+        # Extract tag values, splitting comma-separated lists (e.g. "tag:coffee,brewing")
+        raw_values = re.findall(r"tag:(\S+)", query, flags=re.IGNORECASE)
+        tag_values = [v for raw in raw_values for v in raw.split(",") if v]
+        if tag_values:
+            # Merge with any explicitly provided tags
+            tags = list(set((tags or []) + tag_values))
+            # Remove tag: tokens and boolean connectors, keep remaining text as query
+            remainder = re.sub(r"tag:\S+", "", query, flags=re.IGNORECASE)
+            remainder = re.sub(r"\b(AND|OR|NOT)\b", "", remainder).strip()
+            query = remainder or None
+
     # Detect project from memory URL prefix before routing
-    if project is None:
+    if project is None and query is not None:
         detected = detect_project_from_url_prefix(query, ConfigManager().config)
         if detected:
             project = detected
 
-    async with get_project_client(project, workspace, context) as (client, active_project):
-        # Handle memory:// URLs by resolving to permalink search
-        _, resolved_query, is_memory_url = await resolve_project_and_path(
-            client, query, project, context
-        )
-        effective_search_type = search_type or _default_search_type()
-        if is_memory_url:
-            query = resolved_query
-            effective_search_type = "permalink"
+    with telemetry.operation(
+        "mcp.tool.search_notes",
+        entrypoint="mcp",
+        tool_name="search_notes",
+        requested_project=project,
+        workspace_id=workspace,
+        search_type=search_type or "default",
+        output_format=output_format,
+        page=page,
+        page_size=page_size,
+        has_query=bool(query and query.strip()),
+        note_type_filter_count=len(note_types),
+        entity_type_filter_count=len(entity_types),
+        has_filters=bool(
+            metadata_filters or tags or status or note_types or entity_types or after_date
+        ),
+        has_tags_filter=bool(tags),
+        has_status_filter=bool(status),
+    ):
+        async with get_project_client(project, workspace, context) as (client, active_project):
+            with telemetry.contextualize(
+                project_name=active_project.name,
+                workspace_id=workspace,
+                tool_name="search_notes",
+            ):
+                # Handle memory:// URLs by resolving to permalink search
+                is_memory_url = False
+                if query is not None:
+                    _, resolved_query, is_memory_url = await resolve_project_and_path(
+                        client, query, project, context
+                    )
+                    if is_memory_url:
+                        query = resolved_query
+                effective_search_type = search_type or _default_search_type()
+                if is_memory_url:
+                    effective_search_type = "permalink"
 
-        try:
-            # Create a SearchQuery object based on the parameters
-            search_query = SearchQuery()
+                try:
+                    # Create a SearchQuery object based on the parameters
+                    search_query = SearchQuery()
 
-            # Map search_type to the appropriate query field and retrieval mode
-            valid_search_types = {"text", "title", "permalink", "vector", "semantic", "hybrid"}
-            if effective_search_type == "text":
-                search_query.text = query
-                search_query.retrieval_mode = SearchRetrievalMode.FTS
-            elif effective_search_type in ("vector", "semantic"):
-                search_query.text = query
-                search_query.retrieval_mode = SearchRetrievalMode.VECTOR
-            elif effective_search_type == "hybrid":
-                search_query.text = query
-                search_query.retrieval_mode = SearchRetrievalMode.HYBRID
-            elif effective_search_type == "title":
-                search_query.title = query
-            elif effective_search_type == "permalink" and "*" in query:
-                search_query.permalink_match = query
-            elif effective_search_type == "permalink":
-                search_query.permalink = query
-            else:
-                raise ValueError(
-                    f"Invalid search_type '{effective_search_type}'. "
-                    f"Valid options: {', '.join(sorted(valid_search_types))}"
-                )
+                    # Only map search_type to query fields when there is an actual query string.
+                    # When query is None/empty, skip the search mode block — filters-only path.
+                    effective_query = (query or "").strip()
+                    if effective_query:
+                        valid_search_types = {
+                            "text",
+                            "title",
+                            "permalink",
+                            "vector",
+                            "semantic",
+                            "hybrid",
+                        }
+                        if effective_search_type == "text":
+                            search_query.text = effective_query
+                            search_query.retrieval_mode = SearchRetrievalMode.FTS
+                        elif effective_search_type in ("vector", "semantic"):
+                            search_query.text = effective_query
+                            search_query.retrieval_mode = SearchRetrievalMode.VECTOR
+                        elif effective_search_type == "hybrid":
+                            search_query.text = effective_query
+                            search_query.retrieval_mode = SearchRetrievalMode.HYBRID
+                        elif effective_search_type == "title":
+                            search_query.title = effective_query
+                        elif effective_search_type == "permalink" and "*" in effective_query:
+                            search_query.permalink_match = effective_query
+                        elif effective_search_type == "permalink":
+                            search_query.permalink = effective_query
+                        else:
+                            raise ValueError(
+                                f"Invalid search_type '{effective_search_type}'. "
+                                f"Valid options: {', '.join(sorted(valid_search_types))}"
+                            )
 
-            # Add optional filters if provided (empty lists are treated as no filter)
-            if entity_types:
-                search_query.entity_types = [SearchItemType(t) for t in entity_types]
-            if note_types:
-                search_query.note_types = note_types
-            if after_date:
-                search_query.after_date = after_date
-            if metadata_filters:
-                search_query.metadata_filters = metadata_filters
-            if tags:
-                search_query.tags = tags
-            if status:
-                search_query.status = status
-            if min_similarity is not None:
-                search_query.min_similarity = min_similarity
+                    # Add optional filters if provided (empty lists are treated as no filter)
+                    if entity_types:
+                        search_query.entity_types = [SearchItemType(t) for t in entity_types]
+                    if note_types:
+                        search_query.note_types = note_types
+                    if after_date:
+                        search_query.after_date = after_date
+                    if metadata_filters:
+                        # Alias common column/model names to their frontmatter key equivalents.
+                        # Users often pass "note_type" (the entity model column) when the
+                        # frontmatter field is actually "type".
+                        _METADATA_KEY_ALIASES = {"note_type": "type"}
+                        metadata_filters = {
+                            _METADATA_KEY_ALIASES.get(k, k): v for k, v in metadata_filters.items()
+                        }
+                        search_query.metadata_filters = metadata_filters
+                    if tags:
+                        search_query.tags = tags
+                    if status:
+                        search_query.status = status
+                    if min_similarity is not None:
+                        search_query.min_similarity = min_similarity
 
-            logger.info(f"Searching for {search_query} in project {active_project.name}")
-            # Import here to avoid circular import (tools → clients → utils → tools)
-            from basic_memory.mcp.clients import SearchClient
+                    # Reject searches with no criteria at all
+                    if search_query.no_criteria():
+                        return (
+                            "# No Search Criteria\n\n"
+                            "Please provide at least one of: `query`, `metadata_filters`, "
+                            "`tags`, `status`, `note_types`, `entity_types`, or `after_date`."
+                        )
 
-            # Use typed SearchClient for API calls
-            search_client = SearchClient(client, active_project.external_id)
-            result = await search_client.search(
-                search_query.model_dump(),
-                page=page,
-                page_size=page_size,
-            )
+                    # Default to entity-level results to avoid returning individual
+                    # observations/relations as separate search results (see issue #31).
+                    # Applied after no_criteria() so that the implicit default doesn't
+                    # mask a truly empty search request.
+                    if not search_query.entity_types:
+                        search_query.entity_types = [SearchItemType("entity")]
 
-            # Check if we got no results and provide helpful guidance
-            if not result.results:
-                logger.info(
-                    f"Search returned no results for query: {query} in project {active_project.name}"
-                )
-                # Don't treat this as an error, but the user might want guidance
-                # We return the empty result as normal - the user can decide if they need help
+                    logger.debug(
+                        f"Search request: project={active_project.name} "
+                        f"search_type={effective_search_type} "
+                        f"query={effective_query or '<filters-only>'} "
+                        f"note_types={len(note_types)} entity_types={len(search_query.entity_types or [])} "
+                        f"page={page} page_size={page_size}"
+                    )
+                    # Import here to avoid circular import (tools → clients → utils → tools)
+                    from basic_memory.mcp.clients import SearchClient
 
-            if output_format == "json":
-                return result.model_dump(mode="json", exclude_none=True)
-
-            return result
-
-        except Exception as e:
-            logger.error(f"Search failed for query '{query}': {e}, project: {active_project.name}")
-            # Return formatted error message as string for better user experience
-            return _format_search_error_response(
-                active_project.name, str(e), query, effective_search_type
-            )
-
-
-@mcp.tool(
-    description="Search entities by structured frontmatter metadata.",
-    annotations={"readOnlyHint": True, "openWorldHint": False},
-)
-async def search_by_metadata(
-    filters: Dict[str, Any],
-    project: Optional[str] = None,
-    workspace: Optional[str] = None,
-    limit: int = 20,
-    offset: int = 0,
-    context: Context | None = None,
-) -> SearchResponse | str:
-    """Search entities by structured frontmatter metadata.
-
-    Args:
-        filters: Dictionary of metadata filters (e.g., {"status": "in-progress"})
-        project: Project name to search in. Optional - server will resolve using hierarchy.
-        limit: Maximum number of results to return
-        offset: Number of results to skip (for pagination)
-        context: Optional FastMCP context for performance caching.
-
-    Returns:
-        SearchResponse with results, or helpful error guidance if search fails
-    """
-    if limit <= 0:
-        return "# Error\n\n`limit` must be greater than 0."
-
-    # Build a structured-only search query
-    search_query = SearchQuery()
-    search_query.metadata_filters = filters
-    search_query.entity_types = [SearchItemType.ENTITY]
-
-    # Convert offset/limit to page/page_size (API uses paging)
-    page_size = limit
-    page = (offset // limit) + 1
-    offset_within_page = offset % limit
-
-    async with get_project_client(project, workspace, context) as (client, active_project):
-        logger.info(
-            f"Structured search in project {active_project.name} filters={filters} limit={limit} offset={offset}"
-        )
-
-        try:
-            from basic_memory.mcp.clients import SearchClient
-
-            search_client = SearchClient(client, active_project.external_id)
-            result = await search_client.search(
-                search_query.model_dump(),
-                page=page,
-                page_size=page_size,
-            )
-
-            # Apply offset within page, fetch next page if needed
-            if offset_within_page:
-                remaining = result.results[offset_within_page:]
-                if len(remaining) < limit:
-                    next_page = page + 1
-                    extra = await search_client.search(
+                    # Use typed SearchClient for API calls
+                    search_client = SearchClient(client, active_project.external_id)
+                    result = await search_client.search(
                         search_query.model_dump(),
-                        page=next_page,
+                        page=page,
                         page_size=page_size,
                     )
-                    remaining.extend(extra.results[: max(0, limit - len(remaining))])
-                result = SearchResponse(
-                    results=remaining[:limit],
-                    current_page=page,
-                    page_size=page_size,
-                )
+                    logger.debug(
+                        f"Search response: project={active_project.name} "
+                        f"results={len(result.results)} has_more={str(result.has_more).lower()} "
+                        f"page={result.current_page} page_size={result.page_size}"
+                    )
 
-            return result
+                    # Check if we got no results and provide helpful guidance
+                    if not result.results:
+                        logger.debug(
+                            f"Search returned no results for query: {query} in project {active_project.name}"
+                        )
+                        # Don't treat this as an error, but the user might want guidance
+                        # We return the empty result as normal - the user can decide if they need help
 
-        except Exception as e:
-            logger.error(
-                f"Metadata search failed for filters '{filters}': {e}, project: {active_project.name}"
-            )
-            return _format_search_error_response(
-                active_project.name, str(e), str(filters), "metadata"
-            )
+                    if output_format == "json":
+                        return result.model_dump(mode="json", exclude_none=True)
+
+                    return _format_search_markdown(result, active_project.name, query)
+
+                except Exception as e:
+                    logger.error(
+                        f"Search failed for query '{query or ''}': {e}, project: {active_project.name}"
+                    )
+                    # Return formatted error message as string for better user experience
+                    return _format_search_error_response(
+                        active_project.name, str(e), query or "", effective_search_type
+                    )

src/basic_memory/mcp/tools/ui_sdk.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from typing import Any, Dict, List, Optional
+from typing import Annotated, Any, Dict, List, Optional
 
 from fastmcp import Context
 from mcp.types import ContentBlock, TextContent
@@ -28,8 +28,17 @@ async def search_notes_ui(
     page: int = 1,
     page_size: int = 10,
     search_type: Optional[str] = None,
-    note_types: List[str] | None = None,
-    entity_types: List[str] | None = None,
+    note_types: Annotated[
+        List[str] | None,
+        "Filter by the 'type' field in note frontmatter (e.g. 'note', 'chapter', 'person'). "
+        "Case-insensitive.",
+    ] = None,
+    entity_types: Annotated[
+        List[str] | None,
+        "Filter by knowledge graph item type: 'entity' (whole notes), 'observation', or "
+        "'relation'. Defaults to 'entity'. Do NOT pass schema/frontmatter types like "
+        "'Chapter' here — use note_types instead.",
+    ] = None,
     after_date: Optional[str] = None,
     metadata_filters: Optional[Dict[str, Any]] = None,
     tags: Optional[List[str]] = None,

src/basic_memory/mcp/tools/utils.py

@@ -5,6 +5,7 @@ to the Basic Memory API, with improved error handling and logging.
 """
 
 import typing
+from contextlib import contextmanager
 from typing import Optional
 
 from httpx import Response, URL, AsyncClient, HTTPStatusError
@@ -23,9 +24,62 @@ from httpx._types import (
 from loguru import logger
 from mcp.server.fastmcp.exceptions import ToolError
 
+from basic_memory import telemetry
 from basic_memory.config import ConfigManager
 
 
+def _classify_http_outcome(status_code: int) -> str:
+    """Map HTTP status codes to a low-cardinality outcome label."""
+    if 200 <= status_code < 300:
+        return "success"
+    if 300 <= status_code < 400:  # pragma: no cover
+        return "redirect"
+    if 400 <= status_code < 500:
+        return "client_error"
+    if 500 <= status_code < 600:
+        return "server_error"
+    return "unknown"  # pragma: no cover
+
+
+class _RequestSpan:
+    """Small adapter for attaching outcome metadata to a live request span."""
+
+    def __init__(self, active_span: typing.Any | None):
+        self._active_span = active_span
+
+    def record_response(self, response: Response) -> None:
+        self._set_attributes(
+            {
+                "status_code": response.status_code,
+                "is_success": response.is_success,
+                "outcome": _classify_http_outcome(response.status_code),
+            }
+        )
+
+    def record_transport_error(self, exc: Exception) -> None:
+        self._set_attributes(
+            {
+                "is_success": False,
+                "outcome": "transport_error",
+                "error_type": type(exc).__name__,
+            }
+        )
+
+    def _set_attributes(self, attrs: dict[str, typing.Any]) -> None:
+        if self._active_span is None:
+            return
+
+        set_attributes = getattr(self._active_span, "set_attributes", None)
+        if callable(set_attributes):
+            set_attributes(attrs)
+            return
+
+        set_attribute = getattr(self._active_span, "set_attribute", None)
+        if callable(set_attribute):
+            for key, value in attrs.items():
+                set_attribute(key, value)
+
+
 def get_error_message(
     status_code: int, url: URL | str, method: str, msg: Optional[str] = None
 ) -> str:
@@ -135,10 +189,38 @@ def _resolve_error_message(
     return get_error_message(status_code, url, method)
 
 
+@contextmanager
+def _request_scope(
+    method: str,
+    *,
+    client_name: str | None,
+    operation: str | None,
+    path_template: str | None,
+    params: QueryParamTypes | None = None,
+    has_body: bool = False,
+):
+    """Create the shared MCP transport span used by all HTTP helpers."""
+    attrs = {
+        "method": method,
+        "client_name": client_name,
+        "operation": operation,
+        "path_template": path_template,
+        "phase": "request",
+        "has_query": bool(params),
+        "has_body": has_body,
+    }
+    with telemetry.contextualize(**attrs):
+        with telemetry.started_span("mcp.http.request", **attrs) as active_span:
+            yield _RequestSpan(active_span)
+
+
 async def call_get(
     client: AsyncClient,
     url: URL | str,
     *,
+    client_name: str | None = None,
+    operation: str | None = None,
+    path_template: str | None = None,
     params: QueryParamTypes | None = None,
     headers: HeaderTypes | None = None,
     cookies: CookieTypes | None = None,
@@ -168,18 +250,27 @@ async def call_get(
     """
     logger.debug(f"Calling GET '{url}' params: '{params}'")
     error_message = None
+    request_span: _RequestSpan | None = None
 
     try:
-        response = await client.get(
-            url,
+        with _request_scope(
+            "GET",
+            client_name=client_name,
+            operation=operation,
+            path_template=path_template,
             params=params,
-            headers=headers,
-            cookies=cookies,
-            auth=auth,
-            follow_redirects=follow_redirects,
-            timeout=timeout,
-            extensions=extensions,
-        )
+        ) as request_span:
+            response = await client.get(
+                url,
+                params=params,
+                headers=headers,
+                cookies=cookies,
+                auth=auth,
+                follow_redirects=follow_redirects,
+                timeout=timeout,
+                extensions=extensions,
+            )
+            request_span.record_response(response)
 
         if response.is_success:
             return response
@@ -206,12 +297,19 @@ async def call_get(
 
     except HTTPStatusError as e:
         raise ToolError(error_message) from e
+    except Exception as e:
+        if request_span is not None:
+            request_span.record_transport_error(e)
+        raise
 
 
 async def call_put(
     client: AsyncClient,
     url: URL | str,
     *,
+    client_name: str | None = None,
+    operation: str | None = None,
+    path_template: str | None = None,
     content: RequestContent | None = None,
     data: RequestData | None = None,
     files: RequestFiles | None = None,
@@ -249,22 +347,32 @@ async def call_put(
     """
     logger.debug(f"Calling PUT '{url}'")
     error_message = None
+    request_span: _RequestSpan | None = None
 
     try:
-        response = await client.put(
-            url,
-            content=content,
-            data=data,
-            files=files,
-            json=json,
+        with _request_scope(
+            "PUT",
+            client_name=client_name,
+            operation=operation,
+            path_template=path_template,
             params=params,
-            headers=headers,
-            cookies=cookies,
-            auth=auth,
-            follow_redirects=follow_redirects,
-            timeout=timeout,
-            extensions=extensions,
-        )
+            has_body=any(value is not None for value in (content, data, files, json)),
+        ) as request_span:
+            response = await client.put(
+                url,
+                content=content,
+                data=data,
+                files=files,
+                json=json,
+                params=params,
+                headers=headers,
+                cookies=cookies,
+                auth=auth,
+                follow_redirects=follow_redirects,
+                timeout=timeout,
+                extensions=extensions,
+            )
+            request_span.record_response(response)
 
         if response.is_success:
             return response
@@ -292,12 +400,19 @@ async def call_put(
 
     except HTTPStatusError as e:
         raise ToolError(error_message) from e
+    except Exception as e:
+        if request_span is not None:
+            request_span.record_transport_error(e)
+        raise
 
 
 async def call_patch(
     client: AsyncClient,
     url: URL | str,
     *,
+    client_name: str | None = None,
+    operation: str | None = None,
+    path_template: str | None = None,
     content: RequestContent | None = None,
     data: RequestData | None = None,
     files: RequestFiles | None = None,
@@ -334,22 +449,32 @@ async def call_patch(
         ToolError: If the request fails with an appropriate error message
     """
     logger.debug(f"Calling PATCH '{url}'")
+    request_span: _RequestSpan | None = None
 
     try:
-        response = await client.patch(
-            url,
-            content=content,
-            data=data,
-            files=files,
-            json=json,
+        with _request_scope(
+            "PATCH",
+            client_name=client_name,
+            operation=operation,
+            path_template=path_template,
             params=params,
-            headers=headers,
-            cookies=cookies,
-            auth=auth,
-            follow_redirects=follow_redirects,
-            timeout=timeout,
-            extensions=extensions,
-        )
+            has_body=any(value is not None for value in (content, data, files, json)),
+        ) as request_span:
+            response = await client.patch(
+                url,
+                content=content,
+                data=data,
+                files=files,
+                json=json,
+                params=params,
+                headers=headers,
+                cookies=cookies,
+                auth=auth,
+                follow_redirects=follow_redirects,
+                timeout=timeout,
+                extensions=extensions,
+            )
+            request_span.record_response(response)
 
         if response.is_success:
             return response
@@ -382,12 +507,19 @@ async def call_patch(
         error_message = _resolve_error_message(status_code, url, "PATCH", response_data)
 
         raise ToolError(error_message) from e
+    except Exception as e:
+        if request_span is not None:
+            request_span.record_transport_error(e)
+        raise
 
 
 async def call_post(
     client: AsyncClient,
     url: URL | str,
     *,
+    client_name: str | None = None,
+    operation: str | None = None,
+    path_template: str | None = None,
     content: RequestContent | None = None,
     data: RequestData | None = None,
     files: RequestFiles | None = None,
@@ -425,23 +557,33 @@ async def call_post(
     """
     logger.debug(f"Calling POST '{url}'")
     error_message = None
+    request_span: _RequestSpan | None = None
 
     try:
-        response = await client.post(
-            url=url,
-            content=content,
-            data=data,
-            files=files,
-            json=json,
+        with _request_scope(
+            "POST",
+            client_name=client_name,
+            operation=operation,
+            path_template=path_template,
             params=params,
-            headers=headers,
-            cookies=cookies,
-            auth=auth,
-            follow_redirects=follow_redirects,
-            timeout=timeout,
-            extensions=extensions,
-        )
-        logger.debug(f"response: {response.json()}")
+            has_body=any(value is not None for value in (content, data, files, json)),
+        ) as request_span:
+            response = await client.post(
+                url=url,
+                content=content,
+                data=data,
+                files=files,
+                json=json,
+                params=params,
+                headers=headers,
+                cookies=cookies,
+                auth=auth,
+                follow_redirects=follow_redirects,
+                timeout=timeout,
+                extensions=extensions,
+            )
+            request_span.record_response(response)
+        logger.debug(f"response: {_extract_response_data(response)}")
 
         if response.is_success:
             return response
@@ -468,6 +610,10 @@ async def call_post(
 
     except HTTPStatusError as e:
         raise ToolError(error_message) from e
+    except Exception as e:
+        if request_span is not None:
+            request_span.record_transport_error(e)
+        raise
 
 
 async def resolve_entity_id(client: AsyncClient, project_external_id: str, identifier: str) -> str:
@@ -506,6 +652,9 @@ async def call_delete(
     client: AsyncClient,
     url: URL | str,
     *,
+    client_name: str | None = None,
+    operation: str | None = None,
+    path_template: str | None = None,
     params: QueryParamTypes | None = None,
     headers: HeaderTypes | None = None,
     cookies: CookieTypes | None = None,
@@ -535,18 +684,27 @@ async def call_delete(
     """
     logger.debug(f"Calling DELETE '{url}'")
     error_message = None
+    request_span: _RequestSpan | None = None
 
     try:
-        response = await client.delete(
-            url=url,
+        with _request_scope(
+            "DELETE",
+            client_name=client_name,
+            operation=operation,
+            path_template=path_template,
             params=params,
-            headers=headers,
-            cookies=cookies,
-            auth=auth,
-            follow_redirects=follow_redirects,
-            timeout=timeout,
-            extensions=extensions,
-        )
+        ) as request_span:
+            response = await client.delete(
+                url=url,
+                params=params,
+                headers=headers,
+                cookies=cookies,
+                auth=auth,
+                follow_redirects=follow_redirects,
+                timeout=timeout,
+                extensions=extensions,
+            )
+            request_span.record_response(response)
 
         if response.is_success:
             return response
@@ -573,3 +731,7 @@ async def call_delete(
 
     except HTTPStatusError as e:
         raise ToolError(error_message) from e
+    except Exception as e:
+        if request_span is not None:
+            request_span.record_transport_error(e)
+        raise

src/basic_memory/mcp/tools/write_note.py

@@ -1,22 +1,26 @@
 """Write note tool for Basic Memory MCP server."""
 
-from typing import List, Union, Optional, Literal
+import textwrap
+from typing import Annotated, List, Union, Optional, Literal
 
 from loguru import logger
+from pydantic import BeforeValidator
 
+from basic_memory import telemetry
+from basic_memory.config import ConfigManager
 from basic_memory.mcp.project_context import get_project_client, add_project_metadata
 from basic_memory.mcp.server import mcp
 from fastmcp import Context
 from basic_memory.schemas.base import Entity
-from basic_memory.utils import parse_tags, validate_project_path
+from basic_memory.utils import coerce_dict, parse_tags, validate_project_path
 
 # Define TagType as a Union that can accept either a string or a list of strings or None
 TagType = Union[List[str], str, None]
 
 
 @mcp.tool(
-    description="Create or update a markdown note. Returns a markdown formatted summary of the semantic content.",
-    annotations={"destructiveHint": False, "idempotentHint": True, "openWorldHint": False},
+    description="Create a markdown note. If the note already exists, returns an error by default — pass overwrite=True to replace.",
+    annotations={"destructiveHint": True, "idempotentHint": False, "openWorldHint": False},
 )
 async def write_note(
     title: str,
@@ -26,13 +30,16 @@ async def write_note(
     workspace: Optional[str] = None,
     tags: list[str] | str | None = None,
     note_type: str = "note",
-    metadata: dict | None = None,
+    metadata: Annotated[dict | None, BeforeValidator(coerce_dict)] = None,
+    overwrite: bool | None = None,
     output_format: Literal["text", "json"] = "text",
     context: Context | None = None,
 ) -> str | dict:
     """Write a markdown note to the knowledge base.
 
-    Creates or updates a markdown note with semantic observations and relations.
+    Creates a markdown note with semantic observations and relations.
+    If the note already exists, returns an error by default. Pass overwrite=True
+    to replace the existing note. For incremental updates, use edit_note instead.
 
     Project Resolution:
     Server resolves projects using a unified priority chain (same in local and cloud modes):
@@ -74,6 +81,8 @@ async def write_note(
         metadata: Optional dict of extra frontmatter fields merged into entity_metadata.
                   Useful for schema notes or any note that needs custom YAML frontmatter
                   beyond title/type/tags. Nested dicts are supported.
+        overwrite: If True, replace existing note on conflict. If False, error on conflict.
+                   If None (default), consult write_note_overwrite_default config setting.
         output_format: "text" returns the existing markdown summary. "json" returns
                        machine-readable metadata.
         context: Optional FastMCP context for performance caching.
@@ -106,12 +115,13 @@ async def write_note(
             note_type="guide"
         )
 
-        # Update existing note (same title/directory)
+        # Overwrite an existing note explicitly
         write_note(
             project="my-research",
             title="Meeting Notes",
             directory="meetings",
-            content="# Weekly Standup\\n\\n- [decision] Use PostgreSQL instead #tech"
+            content="# Weekly Standup\\n\\n- [decision] Use PostgreSQL instead #tech",
+            overwrite=True
         )
 
         # Create a schema note with custom frontmatter via metadata
@@ -132,141 +142,204 @@ async def write_note(
         HTTPError: If project doesn't exist or is inaccessible
         SecurityError: If directory path attempts path traversal
     """
-    async with get_project_client(project, workspace, context) as (client, active_project):
-        logger.info(
-            f"MCP tool call tool=write_note project={active_project.name} directory={directory}, title={title}, tags={tags}"
-        )
+    # Resolve overwrite flag: explicit parameter > config default
+    # Trigger: caller omitted the parameter (None)
+    # Why: lets users set a global default without breaking per-call overrides
+    effective_overwrite = (
+        overwrite if overwrite is not None else ConfigManager().config.write_note_overwrite_default
+    )
 
-        # Normalize "/" to empty string for root directory (must happen before validation)
-        if directory == "/":
-            directory = ""
-
-        # Validate directory path to prevent path traversal attacks
-        project_path = active_project.home
-        if directory and not validate_project_path(directory, project_path):
-            logger.warning(
-                "Attempted path traversal attack blocked",
-                directory=directory,
-                project=active_project.name,
-            )
-            if output_format == "json":
-                return {
-                    "title": title,
-                    "permalink": None,
-                    "file_path": None,
-                    "checksum": None,
-                    "action": "created",
-                    "error": "SECURITY_VALIDATION_ERROR",
-                }
-            return f"# Error\n\nDirectory path '{directory}' is not allowed - paths must stay within project boundaries"
-
-        # Process tags using the helper function
-        tag_list = parse_tags(tags)
-
-        # Build entity_metadata from optional metadata, then explicit tags on top
-        # Order matters: explicit tags parameter takes precedence over metadata["tags"]
-        entity_metadata = {}
-        if metadata:
-            entity_metadata.update(metadata)
-        if tag_list:
-            entity_metadata["tags"] = tag_list
-
-        entity = Entity(
-            title=title,
-            directory=directory,
-            note_type=note_type,
-            content_type="text/markdown",
-            content=content,
-            entity_metadata=entity_metadata or None,
-        )
-
-        # Import here to avoid circular import
-        from basic_memory.mcp.clients import KnowledgeClient
-
-        # Use typed KnowledgeClient for API calls
-        knowledge_client = KnowledgeClient(client, active_project.external_id)
-
-        # Try to create the entity first (optimistic create)
-        logger.debug(f"Attempting to create entity permalink={entity.permalink}")
-        action = "Created"  # Default to created
-        try:
-            result = await knowledge_client.create_entity(entity.model_dump(), fast=False)
-            action = "Created"
-        except Exception as e:
-            # If creation failed due to conflict (already exists), try to update
-            if (
-                "409" in str(e)
-                or "conflict" in str(e).lower()
-                or "already exists" in str(e).lower()
+    with telemetry.operation(
+        "mcp.tool.write_note",
+        entrypoint="mcp",
+        tool_name="write_note",
+        requested_project=project,
+        workspace_id=workspace,
+        note_type=note_type,
+        overwrite=effective_overwrite,
+        output_format=output_format,
+    ):
+        async with get_project_client(project, workspace, context) as (client, active_project):
+            with telemetry.contextualize(
+                project_name=active_project.name,
+                workspace_id=workspace,
+                tool_name="write_note",
             ):
-                logger.debug(f"Entity exists, updating instead permalink={entity.permalink}")
-                try:
-                    if not entity.permalink:
-                        raise ValueError(
-                            "Entity permalink is required for updates"
-                        )  # pragma: no cover
-                    entity_id = await knowledge_client.resolve_entity(entity.permalink)
-                    result = await knowledge_client.update_entity(
-                        entity_id, entity.model_dump(), fast=False
+                logger.info(
+                    f"MCP tool call tool=write_note project={active_project.name} directory={directory}, title={title}, tags={tags}"
+                )
+
+                # Normalize "/" to empty string for root directory (must happen before validation)
+                if directory == "/":
+                    directory = ""
+
+                # Validate directory path to prevent path traversal attacks
+                project_path = active_project.home
+                if directory and not validate_project_path(directory, project_path):
+                    logger.warning(
+                        "Attempted path traversal attack blocked",
+                        directory=directory,
+                        project=active_project.name,
                     )
-                    action = "Updated"
-                except Exception as update_error:  # pragma: no cover
-                    # Re-raise the original error if update also fails
-                    raise e from update_error  # pragma: no cover
-            else:
-                # Re-raise if it's not a conflict error
-                raise  # pragma: no cover
-        summary = [
-            f"# {action} note",
-            f"project: {active_project.name}",
-            f"file_path: {result.file_path}",
-            f"permalink: {result.permalink}",
-            f"checksum: {result.checksum[:8] if result.checksum else 'unknown'}",
-        ]
+                    if output_format == "json":
+                        return {
+                            "title": title,
+                            "permalink": None,
+                            "file_path": None,
+                            "checksum": None,
+                            "action": "created",
+                            "error": "SECURITY_VALIDATION_ERROR",
+                        }
+                    return f"# Error\n\nDirectory path '{directory}' is not allowed - paths must stay within project boundaries"
 
-        # Count observations by category
-        categories = {}
-        if result.observations:
-            for obs in result.observations:
-                categories[obs.category] = categories.get(obs.category, 0) + 1
+                # Process tags using the helper function
+                tag_list = parse_tags(tags)
 
-            summary.append("\n## Observations")
-            for category, count in sorted(categories.items()):
-                summary.append(f"- {category}: {count}")
+                # Build entity_metadata from optional metadata, then explicit tags on top
+                # Order matters: explicit tags parameter takes precedence over metadata["tags"]
+                entity_metadata = {}
+                if metadata:
+                    entity_metadata.update(metadata)
+                if tag_list:
+                    entity_metadata["tags"] = tag_list
 
-        # Count resolved/unresolved relations
-        unresolved = 0
-        resolved = 0
-        if result.relations:
-            unresolved = sum(1 for r in result.relations if not r.to_id)
-            resolved = len(result.relations) - unresolved
-
-            summary.append("\n## Relations")
-            summary.append(f"- Resolved: {resolved}")
-            if unresolved:
-                summary.append(f"- Unresolved: {unresolved}")
-                summary.append(
-                    "\nNote: Unresolved relations point to entities that don't exist yet."
-                )
-                summary.append(
-                    "They will be automatically resolved when target entities are created or during sync operations."
+                entity = Entity(
+                    title=title,
+                    directory=directory,
+                    note_type=note_type,
+                    content_type="text/markdown",
+                    content=content,
+                    entity_metadata=entity_metadata or None,
                 )
 
-        if tag_list:
-            summary.append(f"\n## Tags\n- {', '.join(tag_list)}")
+                # Import here to avoid circular import
+                from basic_memory.mcp.clients import KnowledgeClient
 
-        # Log the response with structured data
-        logger.info(
-            f"MCP tool response: tool=write_note project={active_project.name} action={action} permalink={result.permalink} observations_count={len(result.observations)} relations_count={len(result.relations)} resolved_relations={resolved} unresolved_relations={unresolved}"
-        )
-        if output_format == "json":
-            return {
-                "title": result.title,
-                "permalink": result.permalink,
-                "file_path": result.file_path,
-                "checksum": result.checksum,
-                "action": action.lower(),
-            }
+                # Use typed KnowledgeClient for API calls
+                knowledge_client = KnowledgeClient(client, active_project.external_id)
 
-        summary_result = "\n".join(summary)
-        return add_project_metadata(summary_result, active_project.name)
+                # Try to create the entity first (optimistic create)
+                logger.debug(f"Attempting to create entity permalink={entity.permalink}")
+                action = "Created"  # Default to created
+                try:
+                    result = await knowledge_client.create_entity(entity.model_dump(), fast=False)
+                    action = "Created"
+                except Exception as e:
+                    # If creation failed due to conflict (already exists), try to update
+                    if (
+                        "409" in str(e)
+                        or "conflict" in str(e).lower()
+                        or "already exists" in str(e).lower()
+                    ):
+                        # Guard: block overwrite unless explicitly enabled
+                        if not effective_overwrite:
+                            logger.warning(
+                                f"write_note blocked: note already exists (overwrite not enabled) "
+                                f"permalink={entity.permalink}"
+                            )
+                            if output_format == "json":
+                                return {
+                                    "title": title,
+                                    "permalink": entity.permalink,
+                                    "file_path": None,
+                                    "checksum": None,
+                                    "action": "conflict",
+                                    "error": "NOTE_ALREADY_EXISTS",
+                                }
+                            return _format_overwrite_error(
+                                title, entity.permalink, active_project.name
+                            )
+
+                        logger.debug(
+                            f"Entity exists, updating instead permalink={entity.permalink}"
+                        )
+                        try:
+                            if not entity.permalink:
+                                raise ValueError(
+                                    "Entity permalink is required for updates"
+                                )  # pragma: no cover
+                            entity_id = await knowledge_client.resolve_entity(entity.permalink)
+                            result = await knowledge_client.update_entity(
+                                entity_id, entity.model_dump(), fast=False
+                            )
+                            action = "Updated"
+                        except Exception as update_error:  # pragma: no cover
+                            # Re-raise the original error if update also fails
+                            raise e from update_error  # pragma: no cover
+                    else:
+                        # Re-raise if it's not a conflict error
+                        raise  # pragma: no cover
+                summary = [
+                    f"# {action} note",
+                    f"project: {active_project.name}",
+                    f"file_path: {result.file_path}",
+                    f"permalink: {result.permalink}",
+                    f"checksum: {result.checksum[:8] if result.checksum else 'unknown'}",
+                ]
+
+                # Count observations by category
+                categories = {}
+                if result.observations:
+                    for obs in result.observations:
+                        categories[obs.category] = categories.get(obs.category, 0) + 1
+
+                    summary.append("\n## Observations")
+                    for category, count in sorted(categories.items()):
+                        summary.append(f"- {category}: {count}")
+
+                # Count resolved/unresolved relations
+                unresolved = 0
+                resolved = 0
+                if result.relations:
+                    unresolved = sum(1 for r in result.relations if not r.to_id)
+                    resolved = len(result.relations) - unresolved
+
+                    summary.append("\n## Relations")
+                    summary.append(f"- Resolved: {resolved}")
+                    if unresolved:
+                        summary.append(f"- Unresolved: {unresolved}")
+                        summary.append(
+                            "\nNote: Unresolved relations point to entities that don't exist yet."
+                        )
+                        summary.append(
+                            "They will be automatically resolved when target entities are created or during sync operations."
+                        )
+
+                if tag_list:
+                    summary.append(f"\n## Tags\n- {', '.join(tag_list)}")
+
+                # Log the response with structured data
+                logger.info(
+                    f"MCP tool response: tool=write_note project={active_project.name} action={action} permalink={result.permalink} observations_count={len(result.observations)} relations_count={len(result.relations)} resolved_relations={resolved} unresolved_relations={unresolved}"
+                )
+                if output_format == "json":
+                    return {
+                        "title": result.title,
+                        "permalink": result.permalink,
+                        "file_path": result.file_path,
+                        "checksum": result.checksum,
+                        "action": action.lower(),
+                    }
+
+                summary_result = "\n".join(summary)
+                return add_project_metadata(summary_result, active_project.name)
+
+
+def _format_overwrite_error(title: str, permalink: str | None, project_name: str) -> str:
+    """Format a helpful error when write_note is blocked by the overwrite guard."""
+    return textwrap.dedent(f"""\
+        # Error: Note already exists
+
+        **"{title}"** already exists (permalink: `{permalink}`).
+
+        `write_note` does not overwrite by default. Choose an option:
+
+        | Goal | Action |
+        |------|--------|
+        | Append content | `edit_note("{permalink}", operation="append", content="...")` |
+        | Prepend content | `edit_note("{permalink}", operation="prepend", content="...")` |
+        | Replace a section | `edit_note("{permalink}", operation="replace_section", section="...", content="...")` |
+        | Full replace | `write_note("{title}", ..., overwrite=True)` |
+        | Inspect first | `read_note("{permalink}")` |
+
+        Project: {project_name}""")

src/basic_memory/models/search.py

@@ -93,6 +93,27 @@ CREATE VIRTUAL TABLE IF NOT EXISTS search_index USING fts5(
 );
 """)
 
+# Postgres semantic chunk metadata table.
+# Matches the Alembic migration (h1b2c3d4e5f6) schema.
+# Used by tests to create the table without running full migrations.
+CREATE_POSTGRES_SEARCH_VECTOR_CHUNKS_TABLE = DDL("""
+CREATE TABLE IF NOT EXISTS search_vector_chunks (
+    id BIGSERIAL PRIMARY KEY,
+    entity_id INTEGER NOT NULL,
+    project_id INTEGER NOT NULL,
+    chunk_key TEXT NOT NULL,
+    chunk_text TEXT NOT NULL,
+    source_hash TEXT NOT NULL,
+    updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
+    UNIQUE (project_id, entity_id, chunk_key)
+)
+""")
+
+CREATE_POSTGRES_SEARCH_VECTOR_CHUNKS_INDEX = DDL("""
+CREATE INDEX IF NOT EXISTS idx_search_vector_chunks_project_entity
+ON search_vector_chunks (project_id, entity_id)
+""")
+
 # Local semantic chunk metadata table for SQLite.
 # Embedding vectors live in sqlite-vec virtual table keyed by this table rowid.
 CREATE_SQLITE_SEARCH_VECTOR_CHUNKS = DDL("""

src/basic_memory/repository/embedding_provider_factory.py

@@ -1,8 +1,34 @@
 """Factory for creating configured semantic embedding providers."""
 
+from threading import Lock
+
 from basic_memory.config import BasicMemoryConfig
 from basic_memory.repository.embedding_provider import EmbeddingProvider
 
+type ProviderCacheKey = tuple[str, str, int | None, int, str | None, int | None, int | None]
+
+_EMBEDDING_PROVIDER_CACHE: dict[ProviderCacheKey, EmbeddingProvider] = {}
+_EMBEDDING_PROVIDER_CACHE_LOCK = Lock()
+
+
+def _provider_cache_key(app_config: BasicMemoryConfig) -> ProviderCacheKey:
+    """Build a stable cache key from provider-relevant semantic embedding config."""
+    return (
+        app_config.semantic_embedding_provider.strip().lower(),
+        app_config.semantic_embedding_model,
+        app_config.semantic_embedding_dimensions,
+        app_config.semantic_embedding_batch_size,
+        app_config.semantic_embedding_cache_dir,
+        app_config.semantic_embedding_threads,
+        app_config.semantic_embedding_parallel,
+    )
+
+
+def reset_embedding_provider_cache() -> None:
+    """Clear process-level embedding provider cache (used by tests)."""
+    with _EMBEDDING_PROVIDER_CACHE_LOCK:
+        _EMBEDDING_PROVIDER_CACHE.clear()
+
 
 def create_embedding_provider(app_config: BasicMemoryConfig) -> EmbeddingProvider:
     """Create an embedding provider based on semantic config.
@@ -10,32 +36,50 @@ def create_embedding_provider(app_config: BasicMemoryConfig) -> EmbeddingProvide
     When semantic_embedding_dimensions is set in config, it overrides
     the provider's default dimensions (384 for FastEmbed, 1536 for OpenAI).
     """
+    cache_key = _provider_cache_key(app_config)
+    with _EMBEDDING_PROVIDER_CACHE_LOCK:
+        if cached_provider := _EMBEDDING_PROVIDER_CACHE.get(cache_key):
+            return cached_provider
+
     provider_name = app_config.semantic_embedding_provider.strip().lower()
     extra_kwargs: dict = {}
     if app_config.semantic_embedding_dimensions is not None:
         extra_kwargs["dimensions"] = app_config.semantic_embedding_dimensions
 
+    provider: EmbeddingProvider
     if provider_name == "fastembed":
         # Deferred import: fastembed (and its onnxruntime dep) may not be installed
         from basic_memory.repository.fastembed_provider import FastEmbedEmbeddingProvider
 
-        return FastEmbedEmbeddingProvider(
+        if app_config.semantic_embedding_cache_dir is not None:
+            extra_kwargs["cache_dir"] = app_config.semantic_embedding_cache_dir
+        if app_config.semantic_embedding_threads is not None:
+            extra_kwargs["threads"] = app_config.semantic_embedding_threads
+        if app_config.semantic_embedding_parallel is not None:
+            extra_kwargs["parallel"] = app_config.semantic_embedding_parallel
+
+        provider = FastEmbedEmbeddingProvider(
             model_name=app_config.semantic_embedding_model,
             batch_size=app_config.semantic_embedding_batch_size,
             **extra_kwargs,
         )
-
-    if provider_name == "openai":
+    elif provider_name == "openai":
         # Deferred import: openai may not be installed
         from basic_memory.repository.openai_provider import OpenAIEmbeddingProvider
 
         model_name = app_config.semantic_embedding_model or "text-embedding-3-small"
         if model_name == "bge-small-en-v1.5":
             model_name = "text-embedding-3-small"
-        return OpenAIEmbeddingProvider(
+        provider = OpenAIEmbeddingProvider(
             model_name=model_name,
             batch_size=app_config.semantic_embedding_batch_size,
             **extra_kwargs,
         )
+    else:
+        raise ValueError(f"Unsupported semantic embedding provider: {provider_name}")
 
-    raise ValueError(f"Unsupported semantic embedding provider: {provider_name}")
+    with _EMBEDDING_PROVIDER_CACHE_LOCK:
+        if cached_provider := _EMBEDDING_PROVIDER_CACHE.get(cache_key):
+            return cached_provider
+        _EMBEDDING_PROVIDER_CACHE[cache_key] = provider
+        return provider

src/basic_memory/repository/entity_repository.py

@@ -59,16 +59,27 @@ class EntityRepository(Repository[Entity]):
         )
         return await self.find_one(query)
 
-    async def get_by_permalink(self, permalink: str) -> Optional[Entity]:
+    async def _find_one_by_query(self, query, *, load_relations: bool) -> Optional[Entity]:
+        """Return one entity row with optional eager loading."""
+        if load_relations:
+            query = query.options(*self.get_load_options())
+            return await self.find_one(query)
+
+        result = await self.execute_query(query, use_query_options=False)
+        return result.scalars().one_or_none()
+
+    async def get_by_permalink(
+        self, permalink: str, *, load_relations: bool = True
+    ) -> Optional[Entity]:
         """Get entity by permalink.
 
         Args:
             permalink: Unique identifier for the entity
         """
-        query = self.select().where(Entity.permalink == permalink).options(*self.get_load_options())
-        return await self.find_one(query)
+        query = self.select().where(Entity.permalink == permalink)
+        return await self._find_one_by_query(query, load_relations=load_relations)
 
-    async def get_by_title(self, title: str) -> Sequence[Entity]:
+    async def get_by_title(self, title: str, *, load_relations: bool = True) -> Sequence[Entity]:
         """Get entities by title, ordered by shortest path first.
 
         When multiple entities share the same title (in different folders),
@@ -82,23 +93,20 @@ class EntityRepository(Repository[Entity]):
             self.select()
             .where(Entity.title == title)
             .order_by(func.length(Entity.file_path), Entity.file_path)
-            .options(*self.get_load_options())
         )
-        result = await self.execute_query(query)
+        result = await self.execute_query(query, use_query_options=load_relations)
         return list(result.scalars().all())
 
-    async def get_by_file_path(self, file_path: Union[Path, str]) -> Optional[Entity]:
+    async def get_by_file_path(
+        self, file_path: Union[Path, str], *, load_relations: bool = True
+    ) -> Optional[Entity]:
         """Get entity by file_path.
 
         Args:
             file_path: Path to the entity file (will be converted to string internally)
         """
-        query = (
-            self.select()
-            .where(Entity.file_path == Path(file_path).as_posix())
-            .options(*self.get_load_options())
-        )
-        return await self.find_one(query)
+        query = self.select().where(Entity.file_path == Path(file_path).as_posix())
+        return await self._find_one_by_query(query, load_relations=load_relations)
 
     # -------------------------------------------------------------------------
     # Lightweight methods for permalink resolution (no eager loading)
@@ -306,7 +314,7 @@ class EntityRepository(Repository[Entity]):
         result = await self.execute_query(query)
         return list(result.scalars().all())
 
-    async def upsert_entity(self, entity: Entity) -> Entity:
+    async def upsert_entity(self, entity: Entity, *, reload: bool = True) -> Entity:
         """Insert or update entity using simple try/catch with database-level conflict resolution.
 
         Handles file_path race conditions by checking for existing entity on IntegrityError.
@@ -327,6 +335,9 @@ class EntityRepository(Repository[Entity]):
                 session.add(entity)
                 await session.flush()
 
+                if not reload:
+                    return entity
+
                 # Return with relationships loaded
                 query = (
                     self.select()
@@ -363,13 +374,12 @@ class EntityRepository(Repository[Entity]):
                 await session.rollback()
 
                 # Re-query after rollback to get a fresh, attached entity
-                existing_result = await session.execute(
-                    select(Entity)
-                    .where(
-                        Entity.file_path == entity.file_path, Entity.project_id == entity.project_id
-                    )
-                    .options(*self.get_load_options())
+                existing_query = select(Entity).where(
+                    Entity.file_path == entity.file_path, Entity.project_id == entity.project_id
                 )
+                if reload:
+                    existing_query = existing_query.options(*self.get_load_options())
+                existing_result = await session.execute(existing_query)
                 existing_entity = existing_result.scalar_one_or_none()
 
                 if existing_entity:
@@ -393,6 +403,9 @@ class EntityRepository(Repository[Entity]):
 
                     await session.commit()
 
+                    if not reload:
+                        return merged_entity
+
                     # Re-query to get proper relationships loaded
                     final_result = await session.execute(
                         select(Entity)

src/basic_memory/repository/fastembed_provider.py

@@ -5,6 +5,8 @@ from __future__ import annotations
 import asyncio
 from typing import TYPE_CHECKING
 
+from loguru import logger
+
 from basic_memory.repository.embedding_provider import EmbeddingProvider
 from basic_memory.repository.semantic_errors import SemanticDependenciesMissingError
 
@@ -19,16 +21,25 @@ class FastEmbedEmbeddingProvider(EmbeddingProvider):
         "bge-small-en-v1.5": "BAAI/bge-small-en-v1.5",
     }
 
+    def _effective_parallel(self) -> int | None:
+        return self.parallel if self.parallel is not None and self.parallel > 1 else None
+
     def __init__(
         self,
         model_name: str = "bge-small-en-v1.5",
         *,
         batch_size: int = 64,
         dimensions: int = 384,
+        cache_dir: str | None = None,
+        threads: int | None = None,
+        parallel: int | None = None,
     ) -> None:
         self.model_name = model_name
         self.dimensions = dimensions
         self.batch_size = batch_size
+        self.cache_dir = cache_dir
+        self.threads = threads
+        self.parallel = parallel
         self._model: TextEmbedding | None = None
         self._model_lock = asyncio.Lock()
 
@@ -52,9 +63,29 @@ class FastEmbedEmbeddingProvider(EmbeddingProvider):
                         "pip install -U basic-memory"
                     ) from exc
                 resolved_model_name = self._MODEL_ALIASES.get(self.model_name, self.model_name)
+                if self.cache_dir is not None and self.threads is not None:
+                    return TextEmbedding(
+                        model_name=resolved_model_name,
+                        cache_dir=self.cache_dir,
+                        threads=self.threads,
+                    )
+                if self.cache_dir is not None:
+                    return TextEmbedding(model_name=resolved_model_name, cache_dir=self.cache_dir)
+                if self.threads is not None:
+                    return TextEmbedding(model_name=resolved_model_name, threads=self.threads)
                 return TextEmbedding(model_name=resolved_model_name)
 
             self._model = await asyncio.to_thread(_create_model)
+            logger.info(
+                "FastEmbed model loaded: model_name={model_name} batch_size={batch_size} "
+                "threads={threads} configured_parallel={configured_parallel} "
+                "effective_parallel={effective_parallel}",
+                model_name=self._MODEL_ALIASES.get(self.model_name, self.model_name),
+                batch_size=self.batch_size,
+                threads=self.threads,
+                configured_parallel=self.parallel,
+                effective_parallel=self._effective_parallel(),
+            )
             return self._model
 
     async def embed_documents(self, texts: list[str]) -> list[list[float]]:
@@ -62,9 +93,23 @@ class FastEmbedEmbeddingProvider(EmbeddingProvider):
             return []
 
         model = await self._load_model()
+        effective_parallel = self._effective_parallel()
+        logger.debug(
+            "FastEmbed embed_documents call: text_count={text_count} batch_size={batch_size} "
+            "threads={threads} configured_parallel={configured_parallel} "
+            "effective_parallel={effective_parallel}",
+            text_count=len(texts),
+            batch_size=self.batch_size,
+            threads=self.threads,
+            configured_parallel=self.parallel,
+            effective_parallel=effective_parallel,
+        )
 
         def _embed_batch() -> list[list[float]]:
-            vectors = list(model.embed(texts, batch_size=self.batch_size))
+            embed_kwargs: dict[str, int] = {"batch_size": self.batch_size}
+            if effective_parallel is not None:
+                embed_kwargs["parallel"] = effective_parallel
+            vectors = list(model.embed(texts, **embed_kwargs))
             normalized: list[list[float]] = []
             for vector in vectors:
                 values = vector.tolist() if hasattr(vector, "tolist") else vector

src/basic_memory/repository/observation_repository.py

@@ -2,9 +2,10 @@
 
 from typing import Dict, List, Sequence
 
-
 from sqlalchemy import select
 from sqlalchemy.ext.asyncio import async_sessionmaker
+from sqlalchemy.orm import selectinload
+from sqlalchemy.orm.interfaces import LoaderOption
 
 from basic_memory.models import Observation
 from basic_memory.repository.repository import Repository
@@ -22,6 +23,10 @@ class ObservationRepository(Repository[Observation]):
         """
         super().__init__(session_maker, Observation, project_id=project_id)
 
+    def get_load_options(self) -> List[LoaderOption]:
+        """Eager-load parent entity to prevent N+1 if obs.entity is accessed."""
+        return [selectinload(Observation.entity)]
+
     async def find_by_entity(self, entity_id: int) -> Sequence[Observation]:
         """Find all observations for a specific entity."""
         query = select(Observation).filter(Observation.entity_id == entity_id)

src/basic_memory/repository/postgres_search_repository.py

@@ -58,6 +58,9 @@ class PostgresSearchRepository(SearchRepositoryBase):
         self._semantic_enabled = self._app_config.semantic_search_enabled
         self._semantic_vector_k = self._app_config.semantic_vector_k
         self._semantic_min_similarity = self._app_config.semantic_min_similarity
+        self._semantic_embedding_sync_batch_size = (
+            self._app_config.semantic_embedding_sync_batch_size
+        )
         self._embedding_provider = embedding_provider
         self._vector_dimensions = 384
         self._vector_tables_initialized = False
@@ -267,7 +270,7 @@ class PostgresSearchRepository(SearchRepositoryBase):
         if self._vector_tables_initialized:
             return
 
-        logger.info("Ensuring Postgres vector tables exist for semantic search")
+        logger.debug("Ensuring Postgres vector tables exist for semantic search")
 
         async with self._vector_tables_lock:
             if self._vector_tables_initialized:
@@ -358,7 +361,7 @@ class PostgresSearchRepository(SearchRepositoryBase):
                 )
                 await session.commit()
 
-            logger.info(f"Postgres vector tables ready (dimensions={self._vector_dimensions})")
+            logger.debug(f"Postgres vector tables ready (dimensions={self._vector_dimensions})")
             self._vector_tables_initialized = True
 
     async def _get_existing_embedding_dims(self, session: AsyncSession) -> int | None:
@@ -689,9 +692,7 @@ class PostgresSearchRepository(SearchRepositoryBase):
             for idx, note_type in enumerate(note_types):
                 param_name = f"note_type_{idx}"
                 params[param_name] = json.dumps({"note_type": note_type})
-                type_conditions.append(
-                    f"search_index.metadata @> CAST(:{param_name} AS jsonb)"
-                )
+                type_conditions.append(f"search_index.metadata @> CAST(:{param_name} AS jsonb)")
             conditions.append(f"({' OR '.join(type_conditions)})")
 
         # Handle date filter

src/basic_memory/repository/repository.py

@@ -268,8 +268,21 @@ class Repository[T: Base]:
 
             return await self.select_by_ids(session, [model.id for model in model_list])  # pyright: ignore [reportAttributeAccessIssue]
 
-    async def update(self, entity_id: int, entity_data: dict | T) -> Optional[T]:
-        """Update an entity with the given data."""
+    async def update(
+        self,
+        entity_id: int,
+        entity_data: dict | T,
+        *,
+        reload: bool = True,
+    ) -> Optional[T]:
+        """Update an entity with the given data.
+
+        Args:
+            entity_id: Primary key to update
+            entity_data: Column values or a model instance to copy from
+            reload: When True, re-select the entity with repository load options.
+                When False, return the attached row after flush/refresh.
+        """
         logger.debug(f"Updating {self.Model.__name__} {entity_id} with data: {entity_data}")
         async with db.scoped_session(self.session_maker) as session:
             try:
@@ -291,6 +304,8 @@ class Repository[T: Base]:
                 await session.refresh(entity)  # Refresh
 
                 logger.debug(f"Updated {self.Model.__name__}: {entity_id}")
+                if not reload:
+                    return entity
                 return await self.select_by_id(session, entity.id)  # pyright: ignore [reportAttributeAccessIssue]
 
             except NoResultFound:

src/basic_memory/repository/search_index_row.py

@@ -41,7 +41,7 @@ class SearchIndexRow:
     # Matched chunk text from vector search (the actual content that matched the query)
     matched_chunk_text: Optional[str] = None
 
-    CONTENT_DISPLAY_LIMIT = 250
+    CONTENT_DISPLAY_LIMIT = 4000
 
     @property
     def content(self):

src/basic_memory/repository/search_repository.py

@@ -7,7 +7,7 @@ The actual repository implementations are backend-specific:
 """
 
 from datetime import datetime
-from typing import List, Optional, Protocol
+from typing import Any, Callable, List, Optional, Protocol
 
 from sqlalchemy import Result
 from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
@@ -15,6 +15,7 @@ from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
 from basic_memory.config import BasicMemoryConfig, ConfigManager, DatabaseBackend
 from basic_memory.repository.postgres_search_repository import PostgresSearchRepository
 from basic_memory.repository.search_index_row import SearchIndexRow
+from basic_memory.repository.search_repository_base import VectorSyncBatchResult
 from basic_memory.repository.sqlite_search_repository import SQLiteSearchRepository
 from basic_memory.schemas.search import SearchItemType, SearchRetrievalMode
 
@@ -69,6 +70,14 @@ class SearchRepository(Protocol):
         """Sync semantic vector chunks for an entity."""
         ...
 
+    async def sync_entity_vectors_batch(
+        self,
+        entity_ids: list[int],
+        progress_callback: Optional[Callable[[int, int, int], Any]] = None,
+    ) -> VectorSyncBatchResult:
+        """Sync semantic vector chunks for a batch of entities."""
+        ...
+
     async def execute_query(self, query, params: dict) -> Result:
         """Execute a raw SQL query."""
         ...

src/basic_memory/repository/search_repository_base.py

@@ -5,9 +5,9 @@ import json
 import re
 import time
 from abc import ABC, abstractmethod
-from dataclasses import replace
+from dataclasses import dataclass, field, replace
 from datetime import datetime
-from typing import Any, Dict, List, Optional
+from typing import Any, Callable, Dict, List, Optional
 
 from loguru import logger
 from sqlalchemy import Executable, Result, text
@@ -25,20 +25,67 @@ from basic_memory.schemas.search import SearchItemType, SearchRetrievalMode
 # --- Semantic search constants ---
 
 VECTOR_FILTER_SCAN_LIMIT = 50000
-RRF_K = 60
+FUSION_BONUS = 0.3
+FTS_GATE_THRESHOLD = 0.0
 MAX_VECTOR_CHUNK_CHARS = 900
 VECTOR_CHUNK_OVERLAP_CHARS = 120
+TOP_CHUNKS_PER_RESULT = 5
+SMALL_NOTE_CONTENT_LIMIT = 2000
 HEADER_LINE_PATTERN = re.compile(r"^\s*#{1,6}\s+")
 BULLET_PATTERN = re.compile(r"^[\-\*]\s+")
 
 
+@dataclass
+class VectorSyncBatchResult:
+    """Aggregate result for batched semantic vector sync runs."""
+
+    entities_total: int
+    entities_synced: int
+    entities_failed: int
+    failed_entity_ids: list[int] = field(default_factory=list)
+    embedding_jobs_total: int = 0
+    embed_seconds_total: float = 0.0
+    write_seconds_total: float = 0.0
+
+
+@dataclass
+class _PreparedEntityVectorSync:
+    """Prepared chunk mutations + embedding jobs for one entity."""
+
+    entity_id: int
+    sync_start: float
+    source_rows_count: int
+    embedding_jobs: list[tuple[int, str]]
+
+
+@dataclass
+class _PendingEmbeddingJob:
+    """Pending embedding write entry with entity ownership metadata."""
+
+    entity_id: int
+    chunk_row_id: int
+    chunk_text: str
+
+
+@dataclass
+class _EntitySyncRuntime:
+    """Per-entity runtime counters used while flushes are in flight."""
+
+    sync_start: float
+    source_rows_count: int
+    embedding_jobs_count: int
+    remaining_jobs: int
+    embed_seconds: float = 0.0
+    write_seconds: float = 0.0
+
+
 class SearchRepositoryBase(ABC):
     """Abstract base class for backend-specific search repository implementations.
 
     This class defines the common interface that all search repositories must implement,
     regardless of whether they use SQLite FTS5 or Postgres tsvector for full-text search.
 
-    Shared semantic search logic (chunking, embedding orchestration, hybrid RRF fusion)
+    Shared semantic search logic (chunking, embedding orchestration, hybrid score-based fusion)
     lives here. Backend-specific operations are delegated to abstract hooks.
 
     Concrete implementations:
@@ -51,6 +98,7 @@ class SearchRepositoryBase(ABC):
     _semantic_vector_k: int
     _semantic_min_similarity: float
     _embedding_provider: Optional[EmbeddingProvider]
+    _semantic_embedding_sync_batch_size: int
     _vector_dimensions: int
     _vector_tables_initialized: bool
 
@@ -403,21 +451,36 @@ class SearchRepositoryBase(ABC):
         return "\n\n".join(part for part in row_parts if part)
 
     def _build_chunk_records(self, rows) -> list[dict[str, str]]:
-        records: list[dict[str, str]] = []
+        records_by_key: dict[str, dict[str, str]] = {}
+        duplicate_chunk_keys = 0
         for row in rows:
             source_text = self._compose_row_source_text(row)
             chunks = self._split_text_into_chunks(source_text)
             for chunk_index, chunk_text in enumerate(chunks):
                 chunk_key = f"{row.type}:{row.id}:{chunk_index}"
                 source_hash = hashlib.sha256(chunk_text.encode("utf-8")).hexdigest()
-                records.append(
-                    {
-                        "chunk_key": chunk_key,
-                        "chunk_text": chunk_text,
-                        "source_hash": source_hash,
-                    }
-                )
-        return records
+                # Trigger: SQLite FTS5 can accumulate duplicate logical rows for the
+                # same search_index id because it does not enforce relational uniqueness.
+                # Why: duplicate chunk keys would schedule duplicate writes for the same
+                # chunk row and eventually trip UNIQUE(rowid) in search_vector_embeddings.
+                # Outcome: collapse chunk work to one deterministic record per chunk key.
+                if chunk_key in records_by_key:
+                    duplicate_chunk_keys += 1
+                records_by_key[chunk_key] = {
+                    "chunk_key": chunk_key,
+                    "chunk_text": chunk_text,
+                    "source_hash": source_hash,
+                }
+
+        if duplicate_chunk_keys:
+            logger.warning(
+                "Collapsed duplicate vector chunk keys before embedding sync: "
+                "project_id={project_id} duplicate_chunk_keys={duplicate_chunk_keys}",
+                project_id=self.project_id,
+                duplicate_chunk_keys=duplicate_chunk_keys,
+            )
+
+        return list(records_by_key.values())
 
     # --- Text splitting ---
 
@@ -560,15 +623,205 @@ class SearchRepositoryBase(ABC):
     # ------------------------------------------------------------------
 
     async def sync_entity_vectors(self, entity_id: int) -> None:
-        """Sync semantic chunk rows + embeddings for a single entity.
+        """Sync semantic chunk rows + embeddings for a single entity."""
+        await self._sync_entity_vectors_internal(
+            [entity_id],
+            progress_callback=None,
+            continue_on_error=False,
+        )
 
-        This is the shared orchestration logic. Backend-specific SQL operations
-        are delegated to abstract hooks (_delete_entity_chunks, _write_embeddings, etc.).
-        """
+    async def sync_entity_vectors_batch(
+        self,
+        entity_ids: list[int],
+        progress_callback: Optional[Callable[[int, int, int], Any]] = None,
+    ) -> VectorSyncBatchResult:
+        """Sync semantic chunk rows + embeddings for a batch of entities."""
+        return await self._sync_entity_vectors_internal(
+            entity_ids,
+            progress_callback=progress_callback,
+            continue_on_error=True,
+        )
+
+    async def _sync_entity_vectors_internal(
+        self,
+        entity_ids: list[int],
+        progress_callback: Optional[Callable[[int, int, int], Any]],
+        continue_on_error: bool,
+    ) -> VectorSyncBatchResult:
+        """Run shared vector sync orchestration for one or many entities."""
         self._assert_semantic_available()
         await self._ensure_vector_tables()
         assert self._embedding_provider is not None
 
+        total_entities = len(entity_ids)
+        result = VectorSyncBatchResult(
+            entities_total=total_entities,
+            entities_synced=0,
+            entities_failed=0,
+        )
+        if total_entities == 0:
+            return result
+
+        logger.info(
+            "Vector batch sync start: project_id={project_id} entities_total={entities_total} "
+            "sync_batch_size={sync_batch_size}",
+            project_id=self.project_id,
+            entities_total=total_entities,
+            sync_batch_size=self._semantic_embedding_sync_batch_size,
+        )
+
+        pending_jobs: list[_PendingEmbeddingJob] = []
+        entity_runtime: dict[int, _EntitySyncRuntime] = {}
+        failed_entity_ids: set[int] = set()
+        synced_entity_ids: set[int] = set()
+
+        for index, entity_id in enumerate(entity_ids):
+            if progress_callback is not None:
+                progress_callback(entity_id, index, total_entities)
+
+            try:
+                prepared = await self._prepare_entity_vector_jobs(entity_id)
+            except Exception as exc:
+                if not continue_on_error:
+                    raise
+                failed_entity_ids.add(entity_id)
+                logger.warning(
+                    "Vector batch sync entity prepare failed: project_id={project_id} "
+                    "entity_id={entity_id} error={error}",
+                    project_id=self.project_id,
+                    entity_id=entity_id,
+                    error=str(exc),
+                )
+                continue
+
+            embedding_jobs_count = len(prepared.embedding_jobs)
+            result.embedding_jobs_total += embedding_jobs_count
+
+            if embedding_jobs_count == 0:
+                synced_entity_ids.add(entity_id)
+                total_seconds = time.perf_counter() - prepared.sync_start
+                self._log_vector_sync_complete(
+                    entity_id=entity_id,
+                    total_seconds=total_seconds,
+                    embed_seconds=0.0,
+                    write_seconds=0.0,
+                    source_rows_count=prepared.source_rows_count,
+                    embedding_jobs_count=0,
+                )
+                continue
+
+            entity_runtime[entity_id] = _EntitySyncRuntime(
+                sync_start=prepared.sync_start,
+                source_rows_count=prepared.source_rows_count,
+                embedding_jobs_count=embedding_jobs_count,
+                remaining_jobs=embedding_jobs_count,
+            )
+            pending_jobs.extend(
+                _PendingEmbeddingJob(
+                    entity_id=entity_id, chunk_row_id=row_id, chunk_text=chunk_text
+                )
+                for row_id, chunk_text in prepared.embedding_jobs
+            )
+
+            while len(pending_jobs) >= self._semantic_embedding_sync_batch_size:
+                flush_jobs = pending_jobs[: self._semantic_embedding_sync_batch_size]
+                pending_jobs = pending_jobs[self._semantic_embedding_sync_batch_size :]
+                try:
+                    embed_seconds, write_seconds = await self._flush_embedding_jobs(
+                        flush_jobs=flush_jobs,
+                        entity_runtime=entity_runtime,
+                        synced_entity_ids=synced_entity_ids,
+                    )
+                    result.embed_seconds_total += embed_seconds
+                    result.write_seconds_total += write_seconds
+                except Exception as exc:
+                    if not continue_on_error:
+                        raise
+                    affected_entity_ids = sorted({job.entity_id for job in flush_jobs})
+                    failed_entity_ids.update(affected_entity_ids)
+                    for failed_entity_id in affected_entity_ids:
+                        entity_runtime.pop(failed_entity_id, None)
+                    logger.warning(
+                        "Vector batch sync flush failed: project_id={project_id} "
+                        "affected_entities={affected_entities} chunk_count={chunk_count} error={error}",
+                        project_id=self.project_id,
+                        affected_entities=affected_entity_ids,
+                        chunk_count=len(flush_jobs),
+                        error=str(exc),
+                    )
+
+        if pending_jobs:
+            flush_jobs = list(pending_jobs)
+            pending_jobs = []
+            try:
+                embed_seconds, write_seconds = await self._flush_embedding_jobs(
+                    flush_jobs=flush_jobs,
+                    entity_runtime=entity_runtime,
+                    synced_entity_ids=synced_entity_ids,
+                )
+                result.embed_seconds_total += embed_seconds
+                result.write_seconds_total += write_seconds
+            except Exception as exc:
+                if not continue_on_error:
+                    raise
+                affected_entity_ids = sorted({job.entity_id for job in flush_jobs})
+                failed_entity_ids.update(affected_entity_ids)
+                for failed_entity_id in affected_entity_ids:
+                    entity_runtime.pop(failed_entity_id, None)
+                logger.warning(
+                    "Vector batch sync final flush failed: project_id={project_id} "
+                    "affected_entities={affected_entities} chunk_count={chunk_count} error={error}",
+                    project_id=self.project_id,
+                    affected_entities=affected_entity_ids,
+                    chunk_count=len(flush_jobs),
+                    error=str(exc),
+                )
+
+        # Trigger: this should never happen after all flushes succeed.
+        # Why: remaining jobs mean runtime tracking drifted from queued jobs.
+        # Outcome: fail-safe marks these entities as failed to avoid false positives.
+        if entity_runtime:
+            orphan_runtime_entities = sorted(entity_runtime.keys())
+            failed_entity_ids.update(orphan_runtime_entities)
+            logger.warning(
+                "Vector batch sync left unfinished entities after flushes: "
+                "project_id={project_id} unfinished_entities={unfinished_entities}",
+                project_id=self.project_id,
+                unfinished_entities=orphan_runtime_entities,
+            )
+
+        # Keep result counters aligned with successful/failed terminal states.
+        synced_entity_ids.difference_update(failed_entity_ids)
+        result.failed_entity_ids = sorted(failed_entity_ids)
+        result.entities_failed = len(result.failed_entity_ids)
+        result.entities_synced = len(synced_entity_ids)
+
+        logger.info(
+            "Vector batch sync complete: project_id={project_id} entities_total={entities_total} "
+            "entities_synced={entities_synced} entities_failed={entities_failed} "
+            "embedding_jobs_total={embedding_jobs_total} embed_seconds_total={embed_seconds_total:.3f} "
+            "write_seconds_total={write_seconds_total:.3f}",
+            project_id=self.project_id,
+            entities_total=result.entities_total,
+            entities_synced=result.entities_synced,
+            entities_failed=result.entities_failed,
+            embedding_jobs_total=result.embedding_jobs_total,
+            embed_seconds_total=result.embed_seconds_total,
+            write_seconds_total=result.write_seconds_total,
+        )
+
+        return result
+
+    async def _prepare_entity_vector_jobs(self, entity_id: int) -> _PreparedEntityVectorSync:
+        """Prepare chunk mutations and embedding jobs for one entity."""
+        sync_start = time.perf_counter()
+
+        logger.info(
+            "Vector sync start: project_id={project_id} entity_id={entity_id}",
+            project_id=self.project_id,
+            entity_id=entity_id,
+        )
+
         async with db.scoped_session(self.session_maker) as session:
             await self._prepare_vector_session(session)
 
@@ -594,18 +847,49 @@ class SearchRepositoryBase(ABC):
                 },
             )
             rows = row_result.fetchall()
+            source_rows_count = len(rows)
+            built_chunk_records_count = 0
 
             # No search_index rows → delete all chunk/embedding data for this entity.
             if not rows:
+                logger.info(
+                    "Vector sync source prepared: project_id={project_id} entity_id={entity_id} "
+                    "source_rows_count={source_rows_count} "
+                    "built_chunk_records_count={built_chunk_records_count}",
+                    project_id=self.project_id,
+                    entity_id=entity_id,
+                    source_rows_count=source_rows_count,
+                    built_chunk_records_count=built_chunk_records_count,
+                )
                 await self._delete_entity_chunks(session, entity_id)
                 await session.commit()
-                return
+                return _PreparedEntityVectorSync(
+                    entity_id=entity_id,
+                    sync_start=sync_start,
+                    source_rows_count=source_rows_count,
+                    embedding_jobs=[],
+                )
 
             chunk_records = self._build_chunk_records(rows)
+            built_chunk_records_count = len(chunk_records)
+            logger.info(
+                "Vector sync source prepared: project_id={project_id} entity_id={entity_id} "
+                "source_rows_count={source_rows_count} "
+                "built_chunk_records_count={built_chunk_records_count}",
+                project_id=self.project_id,
+                entity_id=entity_id,
+                source_rows_count=source_rows_count,
+                built_chunk_records_count=built_chunk_records_count,
+            )
             if not chunk_records:
                 await self._delete_entity_chunks(session, entity_id)
                 await session.commit()
-                return
+                return _PreparedEntityVectorSync(
+                    entity_id=entity_id,
+                    sync_start=sync_start,
+                    source_rows_count=source_rows_count,
+                    embedding_jobs=[],
+                )
 
             # --- Diff existing chunks against incoming ---
             existing_rows_result = await session.execute(
@@ -617,6 +901,7 @@ class SearchRepositoryBase(ABC):
                 {"project_id": self.project_id, "entity_id": entity_id},
             )
             existing_by_key = {row.chunk_key: row for row in existing_rows_result.fetchall()}
+            existing_chunks_count = len(existing_by_key)
             incoming_hashes = {
                 record["chunk_key"]: record["source_hash"] for record in chunk_records
             }
@@ -625,6 +910,7 @@ class SearchRepositoryBase(ABC):
                 for chunk_key, row in existing_by_key.items()
                 if chunk_key not in incoming_hashes
             ]
+            stale_chunks_count = len(stale_ids)
 
             if stale_ids:
                 await self._delete_stale_chunks(session, stale_ids, entity_id)
@@ -638,6 +924,8 @@ class SearchRepositoryBase(ABC):
                 {"project_id": self.project_id, "entity_id": entity_id},
             )
             orphan_rows = orphan_result.fetchall()
+            orphan_ids = {int(row.id) for row in orphan_rows}
+            orphan_chunks_count = len(orphan_ids)
 
             # --- Upsert changed / new chunks, collect embedding jobs ---
             timestamp_expr = self._timestamp_now_expr()
@@ -648,7 +936,7 @@ class SearchRepositoryBase(ABC):
                 # Trigger: chunk exists and hash matches (no content change)
                 # but chunk has no embedding (orphan from crash).
                 # Outcome: schedule re-embedding without touching chunk metadata.
-                is_orphan = current and any(o.id == current.id for o in orphan_rows)
+                is_orphan = current and int(current.id) in orphan_ids
                 if current and current.source_hash == record["source_hash"] and not is_orphan:
                     continue
 
@@ -691,20 +979,141 @@ class SearchRepositoryBase(ABC):
                 row_id = int(inserted.scalar_one())
                 embedding_jobs.append((row_id, record["chunk_text"]))
 
+            logger.info(
+                "Vector sync diff complete: project_id={project_id} entity_id={entity_id} "
+                "existing_chunks_count={existing_chunks_count} "
+                "stale_chunks_count={stale_chunks_count} "
+                "orphan_chunks_count={orphan_chunks_count} "
+                "embedding_jobs_count={embedding_jobs_count}",
+                project_id=self.project_id,
+                entity_id=entity_id,
+                existing_chunks_count=existing_chunks_count,
+                stale_chunks_count=stale_chunks_count,
+                orphan_chunks_count=orphan_chunks_count,
+                embedding_jobs_count=len(embedding_jobs),
+            )
             await session.commit()
 
-        if not embedding_jobs:
-            return
+        return _PreparedEntityVectorSync(
+            entity_id=entity_id,
+            sync_start=sync_start,
+            source_rows_count=source_rows_count,
+            embedding_jobs=embedding_jobs,
+        )
 
-        texts = [t for _, t in embedding_jobs]
+    async def _flush_embedding_jobs(
+        self,
+        flush_jobs: list[_PendingEmbeddingJob],
+        entity_runtime: dict[int, _EntitySyncRuntime],
+        synced_entity_ids: set[int],
+    ) -> tuple[float, float]:
+        """Embed and persist one queued flush chunk."""
+        if not flush_jobs:
+            return 0.0, 0.0
+        assert self._embedding_provider is not None
+
+        embed_start = time.perf_counter()
+        texts = [job.chunk_text for job in flush_jobs]
         embeddings = await self._embedding_provider.embed_documents(texts)
-        if len(embeddings) != len(embedding_jobs):
+        embed_seconds = time.perf_counter() - embed_start
+        embed_rate = (len(flush_jobs) / embed_seconds) if embed_seconds > 0 else 0.0
+        logger.info(
+            "Vector batch embed flush: project_id={project_id} chunk_count={chunk_count} "
+            "embed_seconds={embed_seconds:.3f} embed_rate_chunks_per_second={embed_rate:.2f}",
+            project_id=self.project_id,
+            chunk_count=len(flush_jobs),
+            embed_seconds=embed_seconds,
+            embed_rate=embed_rate,
+        )
+        if len(embeddings) != len(flush_jobs):
             raise RuntimeError("Embedding provider returned an unexpected number of vectors.")
 
+        write_start = time.perf_counter()
         async with db.scoped_session(self.session_maker) as session:
             await self._prepare_vector_session(session)
-            await self._write_embeddings(session, embedding_jobs, embeddings)
+            write_jobs = [(job.chunk_row_id, job.chunk_text) for job in flush_jobs]
+            await self._write_embeddings(session, write_jobs, embeddings)
             await session.commit()
+        write_seconds = time.perf_counter() - write_start
+        write_rate = (len(flush_jobs) / write_seconds) if write_seconds > 0 else 0.0
+        logger.info(
+            "Vector batch write flush: project_id={project_id} row_count={row_count} "
+            "write_seconds={write_seconds:.3f} write_rate_rows_per_second={write_rate:.2f}",
+            project_id=self.project_id,
+            row_count=len(flush_jobs),
+            write_seconds=write_seconds,
+            write_rate=write_rate,
+        )
+
+        flush_size = len(flush_jobs)
+        entity_job_counts: dict[int, int] = {}
+        for job in flush_jobs:
+            entity_job_counts[job.entity_id] = entity_job_counts.get(job.entity_id, 0) + 1
+
+        for entity_id, entity_job_count in entity_job_counts.items():
+            runtime = entity_runtime.get(entity_id)
+            if runtime is None:
+                continue
+            runtime.remaining_jobs -= entity_job_count
+
+            # Attribute flush wall-clock to entities in proportion to rows written.
+            flush_share = entity_job_count / flush_size
+            runtime.embed_seconds += embed_seconds * flush_share
+            runtime.write_seconds += write_seconds * flush_share
+
+            if runtime.remaining_jobs <= 0:
+                synced_entity_ids.add(entity_id)
+                total_seconds = time.perf_counter() - runtime.sync_start
+                self._log_vector_sync_complete(
+                    entity_id=entity_id,
+                    total_seconds=total_seconds,
+                    embed_seconds=runtime.embed_seconds,
+                    write_seconds=runtime.write_seconds,
+                    source_rows_count=runtime.source_rows_count,
+                    embedding_jobs_count=runtime.embedding_jobs_count,
+                )
+                entity_runtime.pop(entity_id, None)
+
+        return embed_seconds, write_seconds
+
+    def _log_vector_sync_complete(
+        self,
+        *,
+        entity_id: int,
+        total_seconds: float,
+        embed_seconds: float,
+        write_seconds: float,
+        source_rows_count: int,
+        embedding_jobs_count: int,
+    ) -> None:
+        """Log completion and slow-entity warnings with a consistent format."""
+        logger.info(
+            "Vector sync complete: project_id={project_id} entity_id={entity_id} "
+            "total_seconds={total_seconds:.3f} embed_seconds={embed_seconds:.3f} "
+            "write_seconds={write_seconds:.3f} source_rows_count={source_rows_count} "
+            "embedding_jobs_count={embedding_jobs_count}",
+            project_id=self.project_id,
+            entity_id=entity_id,
+            total_seconds=total_seconds,
+            embed_seconds=embed_seconds,
+            write_seconds=write_seconds,
+            source_rows_count=source_rows_count,
+            embedding_jobs_count=embedding_jobs_count,
+        )
+        if total_seconds > 10:
+            logger.warning(
+                "Vector sync slow entity: project_id={project_id} entity_id={entity_id} "
+                "total_seconds={total_seconds:.3f} embed_seconds={embed_seconds:.3f} "
+                "write_seconds={write_seconds:.3f} source_rows_count={source_rows_count} "
+                "embedding_jobs_count={embedding_jobs_count}",
+                project_id=self.project_id,
+                entity_id=entity_id,
+                total_seconds=total_seconds,
+                embed_seconds=embed_seconds,
+                write_seconds=write_seconds,
+                source_rows_count=source_rows_count,
+                embedding_jobs_count=embedding_jobs_count,
+            )
 
     async def _prepare_vector_session(self, session: AsyncSession) -> None:
         """Hook for per-session setup (e.g. loading sqlite-vec extension).
@@ -849,6 +1258,7 @@ class SearchRepositoryBase(ABC):
         min_similarity: Optional[float] = None,
         limit: int,
         offset: int,
+        _emit_observability_log: bool = True,
     ) -> List[SearchIndexRow]:
         """Run vector-only search returning chunk-level results.
 
@@ -859,21 +1269,70 @@ class SearchRepositoryBase(ABC):
         self._assert_semantic_available()
         await self._ensure_vector_tables()
         assert self._embedding_provider is not None
-        query_embedding = await self._embedding_provider.embed_query(search_text.strip())
+        query_text = search_text.strip()
         candidate_limit = max(self._semantic_vector_k, (limit + offset) * 10)
+        query_start = time.perf_counter()
+        embed_start = time.perf_counter()
+        query_embedding = await self._embedding_provider.embed_query(query_text)
+        embed_ms = (time.perf_counter() - embed_start) * 1000
+        vector_query_start = time.perf_counter()
 
         async with db.scoped_session(self.session_maker) as session:
             await self._prepare_vector_session(session)
             vector_rows = await self._run_vector_query(session, query_embedding, candidate_limit)
+        vector_query_ms = (time.perf_counter() - vector_query_start) * 1000
+        vector_row_count = len(vector_rows)
+        hydrate_ms = 0.0
+
+        def _log_vector_summary() -> None:
+            if not _emit_observability_log:
+                return
+
+            total_ms = (time.perf_counter() - query_start) * 1000
+            logger.info(
+                "Semantic query timing: project_id={project_id} retrieval_mode={retrieval_mode} "
+                "query_length={query_length} candidate_limit={candidate_limit} "
+                "vector_row_count={vector_row_count} embed_ms={embed_ms:.2f} "
+                "vector_query_ms={vector_query_ms:.2f} hydrate_ms={hydrate_ms:.2f} "
+                "total_ms={total_ms:.2f}",
+                project_id=self.project_id,
+                retrieval_mode="vector",
+                query_length=len(query_text),
+                candidate_limit=candidate_limit,
+                vector_row_count=vector_row_count,
+                embed_ms=embed_ms,
+                vector_query_ms=vector_query_ms,
+                hydrate_ms=hydrate_ms,
+                total_ms=total_ms,
+            )
+            if total_ms > 2000:
+                logger.warning(
+                    "[SEMANTIC_SLOW_QUERY] Semantic query timing: project_id={project_id} "
+                    "retrieval_mode={retrieval_mode} query_length={query_length} "
+                    "candidate_limit={candidate_limit} vector_row_count={vector_row_count} "
+                    "embed_ms={embed_ms:.2f} vector_query_ms={vector_query_ms:.2f} "
+                    "hydrate_ms={hydrate_ms:.2f} total_ms={total_ms:.2f}",
+                    project_id=self.project_id,
+                    retrieval_mode="vector",
+                    query_length=len(query_text),
+                    candidate_limit=candidate_limit,
+                    vector_row_count=vector_row_count,
+                    embed_ms=embed_ms,
+                    vector_query_ms=vector_query_ms,
+                    hydrate_ms=hydrate_ms,
+                    total_ms=total_ms,
+                )
 
         if not vector_rows:
+            _log_vector_summary()
             return []
 
+        hydrate_start = time.perf_counter()
         # Build per-search_index_row similarity scores from chunk-level results.
         # Each chunk_key encodes the search_index row type and id.
-        # Keep the best similarity (and its chunk text) per search_index row id.
+        # Track the best similarity per row (for ranking) and all chunks (for context).
         similarity_by_si_id: dict[int, float] = {}
-        best_chunk_by_si_id: dict[int, str] = {}
+        chunks_by_si_id: dict[int, list[tuple[float, str]]] = {}
         for row in vector_rows:
             chunk_key = row.get("chunk_key", "")
             distance = float(row["best_distance"])
@@ -887,9 +1346,11 @@ class SearchRepositoryBase(ABC):
             current = similarity_by_si_id.get(si_id)
             if current is None or similarity > current:
                 similarity_by_si_id[si_id] = similarity
-                best_chunk_by_si_id[si_id] = chunk_text
+            chunks_by_si_id.setdefault(si_id, []).append((similarity, chunk_text))
 
         if not similarity_by_si_id:
+            hydrate_ms = (time.perf_counter() - hydrate_start) * 1000
+            _log_vector_summary()
             return []
 
         # Filter out results below the minimum similarity threshold.
@@ -902,6 +1363,8 @@ class SearchRepositoryBase(ABC):
                 k: v for k, v in similarity_by_si_id.items() if v >= effective_min_similarity
             }
             if not similarity_by_si_id:
+                hydrate_ms = (time.perf_counter() - hydrate_start) * 1000
+                _log_vector_summary()
                 return []
 
         # Fetch the actual search_index rows
@@ -947,15 +1410,29 @@ class SearchRepositoryBase(ABC):
             row = search_index_rows.get(si_id)
             if row is None:
                 continue
+
+            # Small notes: return full content so the answer is always present.
+            # Large notes: return top-N most relevant chunks for richer context.
+            content_snippet = row.content_snippet or ""
+            if content_snippet and len(content_snippet) <= SMALL_NOTE_CONTENT_LIMIT:
+                matched_chunk_text = content_snippet
+            else:
+                si_chunks = chunks_by_si_id.get(si_id, [])
+                si_chunks.sort(key=lambda c: c[0], reverse=True)
+                top_texts = [text for _, text in si_chunks[:TOP_CHUNKS_PER_RESULT]]
+                matched_chunk_text = "\n---\n".join(top_texts) if top_texts else None
+
             ranked_rows.append(
                 replace(
                     row,
                     score=similarity,
-                    matched_chunk_text=best_chunk_by_si_id.get(si_id),
+                    matched_chunk_text=matched_chunk_text,
                 )
             )
 
         ranked_rows.sort(key=lambda item: item.score or 0.0, reverse=True)
+        hydrate_ms = (time.perf_counter() - hydrate_start) * 1000
+        _log_vector_summary()
         return ranked_rows[offset : offset + limit]
 
     async def _fetch_entity_rows_by_ids(self, entity_ids: list[int]) -> dict[int, SearchIndexRow]:
@@ -1053,7 +1530,7 @@ class SearchRepositoryBase(ABC):
         return result
 
     # ------------------------------------------------------------------
-    # Shared semantic search: hybrid RRF fusion
+    # Shared semantic search: hybrid score-based fusion
     # ------------------------------------------------------------------
 
     async def _search_hybrid(
@@ -1071,13 +1548,17 @@ class SearchRepositoryBase(ABC):
         limit: int,
         offset: int,
     ) -> List[SearchIndexRow]:
-        """Fuse FTS and vector rankings using reciprocal rank fusion (RRF).
+        """Fuse FTS and vector results using score-based fusion.
 
-        Uses entity_id as the fusion key (not permalink) to correctly handle
-        entities with NULL permalinks.
+        Uses search_index row id as the fusion key. The formula
+        ``max(vec, fts) + FUSION_BONUS * min(vec, fts)`` preserves
+        the dominant signal and rewards dual-source agreement.
         """
         self._assert_semantic_available()
+        query_text = search_text.strip()
+        query_start = time.perf_counter()
         candidate_limit = max(self._semantic_vector_k, (limit + offset) * 10)
+        fts_start = time.perf_counter()
         fts_results = await self.search(
             search_text=search_text,
             permalink=permalink,
@@ -1091,6 +1572,8 @@ class SearchRepositoryBase(ABC):
             limit=candidate_limit,
             offset=0,
         )
+        fts_ms = (time.perf_counter() - fts_start) * 1000
+        vector_start = time.perf_counter()
         vector_results = await self._search_vector_only(
             search_text=search_text,
             permalink=permalink,
@@ -1103,12 +1586,14 @@ class SearchRepositoryBase(ABC):
             min_similarity=min_similarity,
             limit=candidate_limit,
             offset=0,
+            _emit_observability_log=False,
         )
+        vector_ms = (time.perf_counter() - vector_start) * 1000
+        fusion_start = time.perf_counter()
 
-        # Score-weighted RRF fusion keyed on search_index row id.
-        # Multiplies the standard 1/(k+rank) score by the normalized original score
-        # so that high-confidence matches contribute more than weak ones at the same rank.
-        fused_scores: dict[int, float] = {}
+        # --- Score-based fusion keyed on search_index row id ---
+        # FTS scores are normalized to [0, 1] (BM25 is unbounded).
+        # Vector scores are used raw — already calibrated [0, 1] by _distance_to_similarity().
         rows_by_id: dict[int, SearchIndexRow] = {}
 
         # Normalize FTS scores to [0, 1] — handles both SQLite (negative bm25)
@@ -1116,27 +1601,80 @@ class SearchRepositoryBase(ABC):
         fts_abs = [abs(row.score or 0.0) for row in fts_results]
         fts_max = max(fts_abs) if fts_abs else 1.0
 
-        for rank, row in enumerate(fts_results, start=1):
+        fts_scores: dict[int, float] = {}
+        for row in fts_results:
             if row.id is None:
                 continue
             norm = abs(row.score or 0.0) / fts_max if fts_max > 0 else 0.0
-            weight = max(norm, 0.1)  # floor preserves RRF stability
-            fused_scores[row.id] = fused_scores.get(row.id, 0.0) + weight * (1.0 / (RRF_K + rank))
+            # Gate: FTS scores below threshold contribute zero
+            if norm < FTS_GATE_THRESHOLD:
+                norm = 0.0
+            fts_scores[row.id] = norm
             rows_by_id[row.id] = row
 
-        # Vector scores already in [0, 1] from the similarity formula
-        vec_max = max((row.score or 0.0) for row in vector_results) if vector_results else 1.0
-
-        for rank, row in enumerate(vector_results, start=1):
+        vec_scores: dict[int, float] = {}
+        for row in vector_results:
             if row.id is None:
                 continue
-            norm = (row.score or 0.0) / vec_max if vec_max > 0 else 0.0
-            weight = max(norm, 0.1)  # floor preserves RRF stability
-            fused_scores[row.id] = fused_scores.get(row.id, 0.0) + weight * (1.0 / (RRF_K + rank))
+            # Trigger: no re-normalization by vec_max
+            # Why: vector similarity is already calibrated [0, 1]; re-normalizing
+            # inflates weak matches when the entire result set is mediocre
+            vec_scores[row.id] = row.score or 0.0
             rows_by_id[row.id] = row
 
+        # Fuse: max(v, f) + FUSION_BONUS * min(v, f)
+        # Preserves the dominant signal; bonus rewards dual-source agreement.
+        # Output range: [0, 1.3] for dual-source, [0, 1.0] for single-source.
+        fused_scores: dict[int, float] = {}
+        for row_id in fts_scores.keys() | vec_scores.keys():
+            v = vec_scores.get(row_id, 0.0)
+            f = fts_scores.get(row_id, 0.0)
+            fused_scores[row_id] = max(v, f) + FUSION_BONUS * min(v, f)
+
         ranked = sorted(fused_scores.items(), key=lambda item: item[1], reverse=True)
         output: list[SearchIndexRow] = []
         for row_id, fused_score in ranked[offset : offset + limit]:
-            output.append(replace(rows_by_id[row_id], score=fused_score))
+            row = rows_by_id[row_id]
+            # Trigger: FTS-only results have no matched_chunk_text from vector search.
+            # Why: without chunk text, API falls back to truncated content, losing answer text.
+            # Outcome: FTS-only results get full content_snippet as matched_chunk.
+            if row.matched_chunk_text is None and row.content_snippet:
+                row = replace(row, matched_chunk_text=row.content_snippet)
+            output.append(replace(row, score=fused_score))
+        fusion_ms = (time.perf_counter() - fusion_start) * 1000
+        total_ms = (time.perf_counter() - query_start) * 1000
+        logger.info(
+            "Semantic query timing: project_id={project_id} retrieval_mode={retrieval_mode} "
+            "query_length={query_length} candidate_limit={candidate_limit} "
+            "fts_count={fts_count} vector_count={vector_count} fts_ms={fts_ms:.2f} "
+            "vector_ms={vector_ms:.2f} fusion_ms={fusion_ms:.2f} total_ms={total_ms:.2f}",
+            project_id=self.project_id,
+            retrieval_mode="hybrid",
+            query_length=len(query_text),
+            candidate_limit=candidate_limit,
+            fts_count=len(fts_results),
+            vector_count=len(vector_results),
+            fts_ms=fts_ms,
+            vector_ms=vector_ms,
+            fusion_ms=fusion_ms,
+            total_ms=total_ms,
+        )
+        if total_ms > 2500:
+            logger.warning(
+                "[SEMANTIC_SLOW_QUERY] Semantic query timing: project_id={project_id} "
+                "retrieval_mode={retrieval_mode} query_length={query_length} "
+                "candidate_limit={candidate_limit} fts_count={fts_count} "
+                "vector_count={vector_count} fts_ms={fts_ms:.2f} vector_ms={vector_ms:.2f} "
+                "fusion_ms={fusion_ms:.2f} total_ms={total_ms:.2f}",
+                project_id=self.project_id,
+                retrieval_mode="hybrid",
+                query_length=len(query_text),
+                candidate_limit=candidate_limit,
+                fts_count=len(fts_results),
+                vector_count=len(vector_results),
+                fts_ms=fts_ms,
+                vector_ms=vector_ms,
+                fusion_ms=fusion_ms,
+                total_ms=total_ms,
+            )
         return output

src/basic_memory/repository/sqlite_search_repository.py

@@ -52,6 +52,9 @@ class SQLiteSearchRepository(SearchRepositoryBase):
         self._semantic_enabled = self._app_config.semantic_search_enabled
         self._semantic_vector_k = self._app_config.semantic_vector_k
         self._semantic_min_similarity = self._app_config.semantic_min_similarity
+        self._semantic_embedding_sync_batch_size = (
+            self._app_config.semantic_embedding_sync_batch_size
+        )
         self._embedding_provider = embedding_provider
         self._sqlite_vec_lock = asyncio.Lock()
         self._vector_tables_initialized = False
@@ -79,7 +82,7 @@ class SQLiteSearchRepository(SearchRepositoryBase):
         across server restarts. Also creates vector tables when semantic search
         is enabled so missing dependencies are caught at startup, not first query.
         """
-        logger.info("Initializing SQLite FTS5 search index")
+        logger.debug("Initializing SQLite FTS5 search index")
         try:
             async with db.scoped_session(self.session_maker) as session:
                 # Create FTS5 virtual table if it doesn't exist
@@ -378,7 +381,7 @@ class SQLiteSearchRepository(SearchRepositoryBase):
         if self._vector_tables_initialized:
             return
 
-        logger.info("Ensuring SQLite vector tables exist for semantic search")
+        logger.debug("Ensuring SQLite vector tables exist for semantic search")
 
         async with db.scoped_session(self.session_maker) as session:
             await self._ensure_sqlite_vec_loaded(session)
@@ -431,19 +434,24 @@ class SQLiteSearchRepository(SearchRepositoryBase):
             await session.execute(create_sqlite_search_vector_embeddings(self._vector_dimensions))
             await session.commit()
 
-        logger.info(f"SQLite vector tables ready (dimensions={self._vector_dimensions})")
+        logger.debug(f"SQLite vector tables ready (dimensions={self._vector_dimensions})")
         self._vector_tables_initialized = True
 
     async def _prepare_vector_session(self, session: AsyncSession) -> None:
         """Load sqlite-vec extension for the session."""
         await self._ensure_sqlite_vec_loaded(session)
 
+    # sqlite-vec hard limit for knn k parameter
+    SQLITE_VEC_MAX_K = 4096
+
     async def _run_vector_query(
         self,
         session: AsyncSession,
         query_embedding: list[float],
         candidate_limit: int,
     ) -> list[dict]:
+        # Constraint: sqlite-vec enforces k <= 4096 for knn queries
+        vector_k = min(candidate_limit, self.SQLITE_VEC_MAX_K)
         query_embedding_json = json.dumps(query_embedding)
         vector_result = await session.execute(
             text(
@@ -458,12 +466,13 @@ class SQLiteSearchRepository(SearchRepositoryBase):
                 "JOIN search_vector_chunks c ON c.id = vector_matches.rowid "
                 "WHERE c.project_id = :project_id "
                 "ORDER BY best_distance ASC "
-                "LIMIT :vector_k"
+                "LIMIT :candidate_limit"
             ),
             {
                 "query_embedding": query_embedding_json,
                 "project_id": self.project_id,
-                "vector_k": candidate_limit,
+                "vector_k": vector_k,
+                "candidate_limit": candidate_limit,
             },
         )
         return [dict(row) for row in vector_result.mappings().all()]

src/basic_memory/runtime.py

@@ -7,6 +7,7 @@ Composition roots (containers) read ConfigManager and use this module
 to resolve the runtime mode, then pass the result downstream.
 """
 
+import os
 from enum import Enum, auto
 
 
@@ -44,10 +45,16 @@ def resolve_runtime_mode(
     Returns:
         The resolved RuntimeMode
     """
-    # Trigger: test environment is detected
-    # Why: tests need special handling (no file sync, isolated DB)
-    # Outcome: returns TEST mode, skipping cloud mode check
     if is_test_env:
         return RuntimeMode.TEST
 
+    # Trigger: BASIC_MEMORY_CLOUD_MODE env var is set
+    # Why: cloud deployments must not start local file sync — cloud handles
+    #      file storage via S3/Tigris, and the local sync tries to open a
+    #      SQLite/Postgres DB that doesn't exist in the cloud container
+    # Outcome: returns CLOUD mode, skipping file sync initialization
+    cloud_mode = os.getenv("BASIC_MEMORY_CLOUD_MODE", "").lower() in ("1", "true")
+    if cloud_mode:
+        return RuntimeMode.CLOUD
+
     return RuntimeMode.LOCAL

src/basic_memory/schema/parser.py

@@ -14,6 +14,7 @@ Syntax reference:
   EntityName as type (capitalized)  # entity reference
 """
 
+import re
 from dataclasses import dataclass, field
 
 
@@ -124,6 +125,31 @@ def _is_entity_ref_type(type_str: str) -> bool:
     return len(type_str) > 0 and type_str[0].isupper()
 
 
+# --- Enum String Parsing ---
+
+
+def _parse_enum_string(value: str) -> tuple[list[str], str | None]:
+    """Parse a string-typed enum value into enum values and optional description.
+
+    When picoschema enum values are quoted in YAML frontmatter (required when a
+    description follows the list), YAML parses the whole thing as a string. This
+    function extracts the enum values and description from that string.
+
+    Examples:
+        "[active, blocked, done], current state" -> (['active', 'blocked', 'done'], 'current state')
+        "[active, blocked]"                      -> (['active', 'blocked'], None)
+        "active"                                 -> (['active'], None)
+    """
+    # Match bracketed list with optional trailing description
+    m = re.match(r"\[([^\]]+)\](?:\s*,\s*(.+))?", value)
+    if m:
+        items = [item.strip() for item in m.group(1).split(",")]
+        description = m.group(2).strip() if m.group(2) else None
+        return items, description
+    # Plain string — single enum value
+    return [value.strip()], None
+
+
 # --- Main Parser ---
 
 
@@ -147,18 +173,25 @@ def parse_picoschema(yaml_dict: dict) -> list[SchemaField]:
         name, required, is_array, is_enum, is_object = _parse_field_key(key)
 
         # --- Enum fields ---
-        # Trigger: value is a list (e.g., [active, inactive])
-        # Why: enums declare allowed values directly as a YAML list
+        # Trigger: value is a list or a string containing bracketed enum values
+        # Why: enums declare allowed values directly as a YAML list, or as a quoted
+        #   string when a description follows (e.g., "[a, b], desc" must be quoted
+        #   in YAML to avoid parse errors)
         # Outcome: SchemaField with is_enum=True and enum_values populated
         if is_enum:
-            enum_values = value if isinstance(value, list) else [str(value)]
+            description = None
+            if isinstance(value, list):
+                enum_values = [str(v) for v in value]
+            else:
+                enum_values, description = _parse_enum_string(str(value))
             fields.append(
                 SchemaField(
                     name=name,
                     type="enum",
                     required=required,
                     is_enum=True,
-                    enum_values=[str(v) for v in enum_values],
+                    enum_values=enum_values,
+                    description=description,
                 )
             )
             continue

src/basic_memory/schemas/__init__.py

@@ -41,6 +41,7 @@ from basic_memory.schemas.project_info import (
     ProjectStatistics,
     ActivityMetrics,
     SystemStatus,
+    EmbeddingStatus,
     ProjectInfoResponse,
 )
 
@@ -78,6 +79,7 @@ __all__ = [
     "ProjectStatistics",
     "ActivityMetrics",
     "SystemStatus",
+    "EmbeddingStatus",
     "ProjectInfoResponse",
     # Directory
     "DirectoryNode",

src/basic_memory/schemas/base.py

@@ -140,10 +140,12 @@ def validate_timeframe(timeframe: str) -> str:
     if parsed > now:
         raise ValueError("Timeframe cannot be in the future")  # pragma: no cover
 
-    # Could format the duration back to our standard format
-    days = (now - parsed).days
+    # Round to nearest day to handle DST transitions where an hour shift
+    # can cause e.g. "7d" to compute as 6 days + 23 hours
+    total_seconds = (now - parsed).total_seconds()
+    days = round(total_seconds / 86400)
 
-    # Could enforce reasonable limits
+    # Enforce reasonable limits
     if days > 365:
         raise ValueError("Timeframe should be <= 1 year")
 
@@ -176,8 +178,13 @@ ContentType = Annotated[
 ]
 
 
-RelationType = Annotated[str, MinLen(1), MaxLen(200)]
-"""Type of relationship between entities. Always use active voice present tense."""
+RelationType = Annotated[str, MinLen(1)]
+"""Type of relationship between entities. Always use active voice present tense.
+
+The database stores relation_type as an unrestricted string, and response models
+need to tolerate existing long-form values written by LLMs. Keeping an API-only
+200-character cap here causes reads to fail for valid stored data.
+"""
 
 ObservationStr = Annotated[
     str,

src/basic_memory/schemas/cloud.py

@@ -1,7 +1,11 @@
 """Schemas for cloud-related API responses."""
 
+from typing import Literal
+
 from pydantic import BaseModel, Field
 
+type ProjectVisibility = Literal["workspace", "shared", "private"]
+
 
 class TenantMountInfo(BaseModel):
     """Response from /tenant/mount/info endpoint."""
@@ -36,6 +40,10 @@ class CloudProjectCreateRequest(BaseModel):
     name: str = Field(..., description="Project name")
     path: str = Field(..., description="Project path (permalink)")
     set_default: bool = Field(default=False, description="Set as default project")
+    visibility: ProjectVisibility = Field(
+        default="workspace",
+        description="Project visibility for team workspaces",
+    )
 
 
 class CloudProjectCreateResponse(BaseModel):

src/basic_memory/schemas/memory.py

@@ -125,7 +125,8 @@ class EntitySummary(BaseModel):
 
     type: Literal["entity"] = "entity"
     external_id: str  # UUID for v2 API routing
-    entity_id: int  # Database ID for v2 API consistency
+    # COMPAT(v0.18): old clients expect these fields in JSON
+    entity_id: Optional[int] = None
     permalink: Optional[str]
     title: str
     content: Optional[str] = None
@@ -143,18 +144,19 @@ class RelationSummary(BaseModel):
     """Simplified relation representation."""
 
     type: Literal["relation"] = "relation"
-    relation_id: int  # Database ID for v2 API consistency
-    entity_id: Optional[int] = None  # ID of the entity this relation belongs to
+    # COMPAT(v0.18): old clients expect these fields in JSON
+    relation_id: Optional[int] = None
+    entity_id: Optional[int] = None
     title: str
     file_path: str
     permalink: str
     relation_type: str
     from_entity: Optional[str] = None
-    from_entity_id: Optional[int] = None  # ID of source entity
-    from_entity_external_id: Optional[str] = None  # UUID of source entity for v2 API routing
+    from_entity_id: Optional[int] = None
+    from_entity_external_id: Optional[str] = None
     to_entity: Optional[str] = None
-    to_entity_id: Optional[int] = None  # ID of target entity
-    to_entity_external_id: Optional[str] = None  # UUID of target entity for v2 API routing
+    to_entity_id: Optional[int] = None
+    to_entity_external_id: Optional[str] = None
     created_at: Annotated[
         datetime, Field(json_schema_extra={"type": "string", "format": "date-time"})
     ]
@@ -168,10 +170,11 @@ class ObservationSummary(BaseModel):
     """Simplified observation representation."""
 
     type: Literal["observation"] = "observation"
-    observation_id: int  # Database ID for v2 API consistency
-    entity_id: Optional[int] = None  # ID of the entity this observation belongs to
-    entity_external_id: Optional[str] = None  # UUID of parent entity for v2 API routing
-    title: str
+    # COMPAT(v0.18): old clients expect these fields in JSON
+    observation_id: Optional[int] = None
+    entity_id: Optional[int] = None
+    entity_external_id: Optional[str] = None
+    title: Optional[str] = None
     file_path: str
     permalink: str
     category: str
@@ -192,18 +195,17 @@ class MemoryMetadata(BaseModel):
     types: Optional[List[SearchItemType]] = None
     depth: int
     timeframe: Optional[str] = None
-    generated_at: Annotated[
-        datetime, Field(json_schema_extra={"type": "string", "format": "date-time"})
-    ]
-    primary_count: Optional[int] = None  # Changed field name
-    related_count: Optional[int] = None  # Changed field name
-    total_results: Optional[int] = None  # For backward compatibility
+    # COMPAT(v0.18): old clients expect generated_at and total_results in JSON
+    generated_at: Optional[datetime] = None
+    primary_count: Optional[int] = None
+    related_count: Optional[int] = None
+    total_results: Optional[int] = None
     total_relations: Optional[int] = None
     total_observations: Optional[int] = None
 
     @field_serializer("generated_at")
-    def serialize_generated_at(self, dt: datetime) -> str:
-        return dt.isoformat()
+    def serialize_generated_at(self, dt: Optional[datetime]) -> Optional[str]:
+        return dt.isoformat() if dt else None
 
 
 class ContextResult(BaseModel):

src/basic_memory/schemas/project_info.py

@@ -79,6 +79,28 @@ class SystemStatus(BaseModel):
     timestamp: datetime = Field(description="Timestamp when the information was collected")
 
 
+class EmbeddingStatus(BaseModel):
+    """Embedding/vector index status for a project."""
+
+    # Config
+    semantic_search_enabled: bool
+    embedding_provider: Optional[str] = None
+    embedding_model: Optional[str] = None
+    embedding_dimensions: Optional[int] = None
+
+    # Counts
+    total_indexed_entities: int = 0
+    total_entities_with_chunks: int = 0
+    total_chunks: int = 0
+    total_embeddings: int = 0
+    orphaned_chunks: int = 0
+    vector_tables_exist: bool = False
+
+    # Derived
+    reindex_recommended: bool = False
+    reindex_reason: Optional[str] = None
+
+
 class ProjectInfoResponse(BaseModel):
     """Response for the project_info tool."""
 
@@ -99,6 +121,11 @@ class ProjectInfoResponse(BaseModel):
     # System status
     system: SystemStatus = Field(description="System and service status information")
 
+    # Embedding status
+    embedding_status: Optional[EmbeddingStatus] = Field(
+        default=None, description="Embedding/vector index status"
+    )
+
 
 class ProjectInfoRequest(BaseModel):
     """Request model for switching projects."""

src/basic_memory/schemas/request.py

@@ -65,7 +65,14 @@ class EditEntityRequest(BaseModel):
     Supports various operation types for different editing scenarios.
     """
 
-    operation: Literal["append", "prepend", "find_replace", "replace_section"]
+    operation: Literal[
+        "append",
+        "prepend",
+        "find_replace",
+        "replace_section",
+        "insert_before_section",
+        "insert_after_section",
+    ]
     content: str
     section: Optional[str] = None
     find_text: Optional[str] = None
@@ -75,8 +82,16 @@ class EditEntityRequest(BaseModel):
     @classmethod
     def validate_section_for_replace_section(cls, v, info):
         """Ensure section is provided for replace_section operation."""
-        if info.data.get("operation") == "replace_section" and not v:
-            raise ValueError("section parameter is required for replace_section operation")
+        if (
+            info.data.get("operation")
+            in (
+                "replace_section",
+                "insert_before_section",
+                "insert_after_section",
+            )
+            and not v
+        ):
+            raise ValueError("section parameter is required for section-based operations")
         return v
 
     @field_validator("find_text")

src/basic_memory/schemas/response.py

@@ -14,7 +14,7 @@ Key Features:
 from datetime import datetime
 from typing import List, Optional, Dict
 
-from pydantic import BaseModel, ConfigDict, Field, model_validator
+from pydantic import BaseModel, ConfigDict, Field, computed_field, model_validator
 
 from basic_memory.schemas.base import Relation, Permalink, NoteType, ContentType, Observation
 
@@ -192,6 +192,13 @@ class EntityResponse(SQLAlchemyModel):
     title: str
     file_path: str
     note_type: NoteType
+
+    # COMPAT(v0.18): old clients expect entity_type; remove when no longer needed
+    @computed_field  # type: ignore[prop-decorator]
+    @property
+    def entity_type(self) -> str:
+        return self.note_type
+
     entity_metadata: Optional[Dict] = None
     checksum: Optional[str] = None
     content_type: ContentType

src/basic_memory/schemas/v2/__init__.py

@@ -10,6 +10,11 @@ from basic_memory.schemas.v2.entity import (
     ProjectResolveRequest,
     ProjectResolveResponse,
 )
+from basic_memory.schemas.v2.graph import (
+    GraphEdge,
+    GraphNode,
+    GraphResponse,
+)
 from basic_memory.schemas.v2.resource import (
     CreateResourceRequest,
     UpdateResourceRequest,
@@ -25,6 +30,9 @@ __all__ = [
     "DeleteDirectoryRequestV2",
     "ProjectResolveRequest",
     "ProjectResolveResponse",
+    "GraphEdge",
+    "GraphNode",
+    "GraphResponse",
     "CreateResourceRequest",
     "UpdateResourceRequest",
     "ResourceResponse",

src/basic_memory/schemas/v2/graph.py

@@ -0,0 +1,31 @@
+"""Graph visualization schemas for the knowledge graph endpoint."""
+
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class GraphNode(BaseModel):
+    """A node in the knowledge graph visualization."""
+
+    external_id: str = Field(..., description="Entity external ID (UUID)")
+    title: str = Field(..., description="Entity title")
+    note_type: Optional[str] = Field(None, description="Note type (e.g., note, spec, task)")
+    file_path: str = Field(..., description="Relative file path")
+
+
+class GraphEdge(BaseModel):
+    """An edge in the knowledge graph visualization."""
+
+    from_id: str = Field(..., description="External ID of source entity")
+    to_id: str = Field(..., description="External ID of target entity")
+    relation_type: str = Field(..., description="Type of relation")
+
+
+class GraphResponse(BaseModel):
+    """Complete knowledge graph for visualization."""
+
+    nodes: list[GraphNode] = Field(default_factory=list, description="All entities as nodes")
+    edges: list[GraphEdge] = Field(
+        default_factory=list, description="All resolved relations as edges"
+    )

src/basic_memory/services/context_service.py

@@ -10,6 +10,7 @@ from typing import List, Optional, Tuple, TYPE_CHECKING
 from loguru import logger
 from sqlalchemy import text
 
+from basic_memory import telemetry
 from basic_memory.repository.entity_repository import EntityRepository
 from basic_memory.repository.observation_repository import ObservationRepository
 from basic_memory.repository.postgres_search_repository import PostgresSearchRepository
@@ -110,146 +111,162 @@ class ContextService:
             f"Building context for URI: '{memory_url}' depth: '{depth}' since: '{since}' limit: '{limit}' offset: '{offset}'  max_related: '{max_related}'"
         )
 
-        # Fetch one extra item to detect whether more pages exist (N+1 trick)
-        fetch_limit = limit + 1
+        with telemetry.scope(
+            "memory.build_context",
+            domain="memory",
+            action="build_context",
+            phase="build_context",
+            limit=limit,
+            offset=offset,
+        ):
+            fetch_limit = limit + 1
 
-        normalized_path: Optional[str] = None
-        if memory_url:
-            path = memory_url_path(memory_url)
-            # Check for wildcards before normalization
-            has_wildcard = "*" in path
+            normalized_path: Optional[str] = None
+            with telemetry.scope(
+                "memory.build_context.resolve_primary",
+                domain="memory",
+                action="build_context",
+                phase="resolve_primary",
+            ):
+                if memory_url:
+                    path = memory_url_path(memory_url)
+                    has_wildcard = "*" in path
 
-            if has_wildcard:
-                # For wildcard patterns, normalize each segment separately to preserve the *
-                parts = path.split("*")
-                normalized_parts = [
-                    generate_permalink(part, split_extension=False) if part else ""
-                    for part in parts
-                ]
-                normalized_path = "*".join(normalized_parts)
-                logger.debug(f"Pattern search for '{normalized_path}'")
-                primary = await self.search_repository.search(
-                    permalink_match=normalized_path, limit=fetch_limit, offset=offset
-                )
-            else:
-                # For exact paths, normalize the whole thing
-                normalized_path = generate_permalink(path, split_extension=False)
-                logger.debug(f"Direct lookup for '{normalized_path}'")
-                primary = await self.search_repository.search(
-                    permalink=normalized_path, limit=fetch_limit, offset=offset
-                )
-
-                # Trigger: exact permalink lookup returned no results
-                # Why: the identifier may be valid but not an exact permalink match
-                #      (e.g., missing project prefix, title instead of permalink)
-                # Outcome: use LinkResolver's multi-strategy resolution to find the entity,
-                #          then retry search with its actual permalink
-                if not primary and self.link_resolver:
-                    entity = await self.link_resolver.resolve_link(
-                        path, use_search=True, strict=False
-                    )
-                    if entity:
-                        logger.debug(
-                            f"LinkResolver resolved '{path}' to permalink '{entity.permalink}'"
-                        )
-                        normalized_path = entity.permalink
+                    if has_wildcard:
+                        parts = path.split("*")
+                        normalized_parts = [
+                            generate_permalink(part, split_extension=False) if part else ""
+                            for part in parts
+                        ]
+                        normalized_path = "*".join(normalized_parts)
+                        logger.debug(f"Pattern search for '{normalized_path}'")
                         primary = await self.search_repository.search(
-                            permalink=entity.permalink, limit=fetch_limit, offset=offset
+                            permalink_match=normalized_path, limit=fetch_limit, offset=offset
                         )
-        else:
-            logger.debug(f"Build context for '{types}'")
-            primary = await self.search_repository.search(
-                search_item_types=types, after_date=since, limit=fetch_limit, offset=offset
+                    else:
+                        normalized_path = generate_permalink(path, split_extension=False)
+                        logger.debug(f"Direct lookup for '{normalized_path}'")
+                        primary = await self.search_repository.search(
+                            permalink=normalized_path, limit=fetch_limit, offset=offset
+                        )
+
+                        if not primary and self.link_resolver:
+                            entity = await self.link_resolver.resolve_link(
+                                path, use_search=True, strict=False
+                            )
+                            if entity:
+                                logger.debug(
+                                    f"LinkResolver resolved '{path}' to permalink '{entity.permalink}'"
+                                )
+                                normalized_path = entity.permalink
+                                primary = await self.search_repository.search(
+                                    permalink=entity.permalink,
+                                    limit=fetch_limit,
+                                    offset=offset,
+                                )
+                else:
+                    logger.debug(f"Build context for '{types}'")
+                    primary = await self.search_repository.search(
+                        search_item_types=types,
+                        after_date=since,
+                        limit=fetch_limit,
+                        offset=offset,
+                    )
+
+            has_more = len(primary) > limit
+            if has_more:
+                primary = primary[:limit]
+
+            type_id_pairs = [(r.type, r.id) for r in primary] if primary else []
+            logger.debug(f"found primary type_id_pairs: {len(type_id_pairs)}")
+
+            with telemetry.scope(
+                "memory.build_context.find_related",
+                domain="memory",
+                action="build_context",
+                phase="find_related",
+            ):
+                related = await self.find_related(
+                    type_id_pairs, max_depth=depth, since=since, max_results=max_related
+                )
+            logger.debug(f"Found {len(related)} related results")
+
+            entity_ids = []
+            for result in primary:
+                if result.type == SearchItemType.ENTITY.value:
+                    entity_ids.append(result.id)
+
+            for result in related:
+                if result.type == SearchItemType.ENTITY.value:
+                    entity_ids.append(result.id)
+
+            observations_by_entity = {}
+            if include_observations and entity_ids:
+                with telemetry.scope(
+                    "memory.build_context.load_observations",
+                    domain="memory",
+                    action="build_context",
+                    phase="load_observations",
+                    result_count=len(entity_ids),
+                ):
+                    observations_by_entity = await self.observation_repository.find_by_entities(
+                        entity_ids
+                    )
+                logger.debug(f"Found observations for {len(observations_by_entity)} entities")
+
+            metadata = ContextMetadata(
+                uri=normalized_path if memory_url else None,
+                types=types,
+                depth=depth,
+                timeframe=since.isoformat() if since else None,
+                primary_count=len(primary),
+                related_count=len(related),
+                total_observations=sum(len(obs) for obs in observations_by_entity.values()),
+                total_relations=sum(1 for r in related if r.type == SearchItemType.RELATION),
+                has_more=has_more,
             )
 
-        # Trim to requested limit and set has_more flag
-        has_more = len(primary) > limit
-        if has_more:
-            primary = primary[:limit]
+            with telemetry.scope(
+                "memory.build_context.shape_results",
+                domain="memory",
+                action="build_context",
+                phase="shape_results",
+                result_count=len(primary),
+            ):
+                context_results = []
+                for primary_item in primary:
+                    related_to_primary = [r for r in related if r.root_id == primary_item.id]
 
-        # Get type_id pairs for traversal
+                    item_observations = []
+                    if primary_item.type == SearchItemType.ENTITY.value and include_observations:
+                        for obs in observations_by_entity.get(primary_item.id, []):
+                            item_observations.append(
+                                ContextResultRow(
+                                    type="observation",
+                                    id=obs.id,
+                                    title=f"{obs.category}: {obs.content[:50]}...",
+                                    permalink=generate_permalink(
+                                        f"{primary_item.permalink}/observations/{obs.category}/{obs.content}"
+                                    ),
+                                    file_path=primary_item.file_path,
+                                    content=obs.content,
+                                    category=obs.category,
+                                    entity_id=primary_item.id,
+                                    depth=0,
+                                    root_id=primary_item.id,
+                                    created_at=primary_item.created_at,
+                                )
+                            )
 
-        type_id_pairs = [(r.type, r.id) for r in primary] if primary else []
-        logger.debug(f"found primary type_id_pairs: {len(type_id_pairs)}")
-
-        # Find related content
-        related = await self.find_related(
-            type_id_pairs, max_depth=depth, since=since, max_results=max_related
-        )
-        logger.debug(f"Found {len(related)} related results")
-
-        # Collect entity IDs from primary and related results
-        entity_ids = []
-        for result in primary:
-            if result.type == SearchItemType.ENTITY.value:
-                entity_ids.append(result.id)
-
-        for result in related:
-            if result.type == SearchItemType.ENTITY.value:
-                entity_ids.append(result.id)
-
-        # Fetch observations for all entities if requested
-        observations_by_entity = {}
-        if include_observations and entity_ids:
-            # Use our observation repository to get observations for all entities at once
-            observations_by_entity = await self.observation_repository.find_by_entities(entity_ids)
-            logger.debug(f"Found observations for {len(observations_by_entity)} entities")
-
-        # Create metadata dataclass
-        metadata = ContextMetadata(
-            uri=normalized_path if memory_url else None,
-            types=types,
-            depth=depth,
-            timeframe=since.isoformat() if since else None,
-            primary_count=len(primary),
-            related_count=len(related),
-            total_observations=sum(len(obs) for obs in observations_by_entity.values()),
-            total_relations=sum(1 for r in related if r.type == SearchItemType.RELATION),
-            has_more=has_more,
-        )
-
-        # Build context results list directly with ContextResultItem objects
-        context_results = []
-
-        # For each primary result
-        for primary_item in primary:
-            # Find all related items with this primary item as root
-            related_to_primary = [r for r in related if r.root_id == primary_item.id]
-
-            # Get observations for this item if it's an entity
-            item_observations = []
-            if primary_item.type == SearchItemType.ENTITY.value and include_observations:
-                # Convert Observation models to ContextResultRows
-                for obs in observations_by_entity.get(primary_item.id, []):
-                    item_observations.append(
-                        ContextResultRow(
-                            type="observation",
-                            id=obs.id,
-                            title=f"{obs.category}: {obs.content[:50]}...",
-                            permalink=generate_permalink(
-                                f"{primary_item.permalink}/observations/{obs.category}/{obs.content}"
-                            ),
-                            file_path=primary_item.file_path,
-                            content=obs.content,
-                            category=obs.category,
-                            entity_id=primary_item.id,
-                            depth=0,
-                            root_id=primary_item.id,
-                            created_at=primary_item.created_at,  # created_at time from entity
+                    context_results.append(
+                        ContextResultItem(
+                            primary_result=primary_item,
+                            observations=item_observations,
+                            related_results=related_to_primary,
                         )
                     )
 
-            # Create ContextResultItem directly
-            context_item = ContextResultItem(
-                primary_result=primary_item,
-                observations=item_observations,
-                related_results=related_to_primary,
-            )
-
-            context_results.append(context_item)
-
-        # Return the structured ContextResult
-        return ContextResult(results=context_results, metadata=metadata)
+            return ContextResult(results=context_results, metadata=metadata)
 
     async def find_related(
         self,

src/basic_memory/services/file_service.py

@@ -11,6 +11,7 @@ import aiofiles
 
 import yaml
 
+from basic_memory import telemetry
 from basic_memory import file_utils
 
 if TYPE_CHECKING:  # pragma: no cover
@@ -79,13 +80,18 @@ class FileService:
         """
         logger.debug(f"Reading entity content, entity_id={entity.id}, permalink={entity.permalink}")
 
-        # markdown_processor is required for entity content reads — fail fast if not configured
-        if self.markdown_processor is None:
-            raise ValueError("markdown_processor is required for read_entity_content")
+        with telemetry.scope(
+            "file_service.read_content",
+            domain="file_service",
+            action="read_content",
+            phase="read_content",
+        ):
+            if self.markdown_processor is None:
+                raise ValueError("markdown_processor is required for read_entity_content")
 
-        file_path = self.get_entity_path(entity)
-        markdown = await self.markdown_processor.read_file(file_path)
-        return markdown.content or ""
+            file_path = self.get_entity_path(entity)
+            markdown = await self.markdown_processor.read_file(file_path)
+            return markdown.content or ""
 
     async def delete_entity_file(self, entity: EntityModel) -> None:
         """Delete entity file from filesystem.
@@ -176,32 +182,34 @@ class FileService:
         full_path = path_obj if path_obj.is_absolute() else self.base_path / path_obj
 
         try:
-            # Ensure parent directory exists
-            await self.ensure_directory(full_path.parent)
+            with telemetry.scope(
+                "file_service.write",
+                domain="file_service",
+                action="write",
+                phase="write",
+            ):
+                await self.ensure_directory(full_path.parent)
 
-            # Write content atomically
-            logger.info(
-                "Writing file: "
-                f"path={path_obj}, "
-                f"content_length={len(content)}, "
-                f"is_markdown={full_path.suffix.lower() == '.md'}"
-            )
-
-            await file_utils.write_file_atomic(full_path, content)
-
-            # Format file if configured
-            final_content = content
-            if self.app_config:
-                formatted_content = await file_utils.format_file(
-                    full_path, self.app_config, is_markdown=self.is_markdown(path)
+                logger.info(
+                    "Writing file: "
+                    f"path={path_obj}, "
+                    f"content_length={len(content)}, "
+                    f"is_markdown={full_path.suffix.lower() == '.md'}"
                 )
-                if formatted_content is not None:
-                    final_content = formatted_content  # pragma: no cover
 
-            # Compute and return checksum of final content
-            checksum = await file_utils.compute_checksum(final_content)
-            logger.debug(f"File write completed path={full_path}, {checksum=}")
-            return checksum
+                await file_utils.write_file_atomic(full_path, content)
+
+                final_content = content
+                if self.app_config:
+                    formatted_content = await file_utils.format_file(
+                        full_path, self.app_config, is_markdown=self.is_markdown(path)
+                    )
+                    if formatted_content is not None:
+                        final_content = formatted_content  # pragma: no cover
+
+                checksum = await file_utils.compute_checksum(final_content)
+                logger.debug(f"File write completed path={full_path}, {checksum=}")
+                return checksum
 
         except Exception as e:
             logger.exception("File write error", path=str(full_path), error=str(e))
@@ -227,16 +235,24 @@ class FileService:
         full_path = path_obj if path_obj.is_absolute() else self.base_path / path_obj
 
         try:
-            logger.debug("Reading file content", operation="read_file_content", path=str(full_path))
-            async with aiofiles.open(full_path, mode="r", encoding="utf-8") as f:
-                content = await f.read()
+            with telemetry.scope(
+                "file_service.read_content",
+                domain="file_service",
+                action="read_content",
+                phase="read_content",
+            ):
+                logger.debug(
+                    "Reading file content", operation="read_file_content", path=str(full_path)
+                )
+                async with aiofiles.open(full_path, mode="r", encoding="utf-8") as f:
+                    content = await f.read()
 
-            logger.debug(
-                "File read completed",
-                path=str(full_path),
-                content_length=len(content),
-            )
-            return content
+                logger.debug(
+                    "File read completed",
+                    path=str(full_path),
+                    content_length=len(content),
+                )
+                return content
 
         except FileNotFoundError:
             # Preserve FileNotFoundError so callers (e.g. sync) can treat it as deletion.
@@ -266,16 +282,22 @@ class FileService:
         full_path = path_obj if path_obj.is_absolute() else self.base_path / path_obj
 
         try:
-            logger.debug("Reading file bytes", operation="read_file_bytes", path=str(full_path))
-            async with aiofiles.open(full_path, mode="rb") as f:
-                content = await f.read()
+            with telemetry.scope(
+                "file_service.read_content",
+                domain="file_service",
+                action="read_content",
+                phase="read_content",
+            ):
+                logger.debug("Reading file bytes", operation="read_file_bytes", path=str(full_path))
+                async with aiofiles.open(full_path, mode="rb") as f:
+                    content = await f.read()
 
-            logger.debug(
-                "File read completed",
-                path=str(full_path),
-                content_length=len(content),
-            )
-            return content
+                logger.debug(
+                    "File read completed",
+                    path=str(full_path),
+                    content_length=len(content),
+                )
+                return content
 
         except Exception as e:
             logger.exception("File read error", path=str(full_path), error=str(e))
@@ -303,21 +325,26 @@ class FileService:
         full_path = path_obj if path_obj.is_absolute() else self.base_path / path_obj
 
         try:
-            logger.debug("Reading file", operation="read_file", path=str(full_path))
+            with telemetry.scope(
+                "file_service.read",
+                domain="file_service",
+                action="read",
+                phase="read",
+            ):
+                logger.debug("Reading file", operation="read_file", path=str(full_path))
 
-            # Use aiofiles for non-blocking read
-            async with aiofiles.open(full_path, mode="r", encoding="utf-8") as f:
-                content = await f.read()
+                async with aiofiles.open(full_path, mode="r", encoding="utf-8") as f:
+                    content = await f.read()
 
-            checksum = await file_utils.compute_checksum(content)
+                checksum = await file_utils.compute_checksum(content)
 
-            logger.debug(
-                "File read completed",
-                path=str(full_path),
-                checksum=checksum,
-                content_length=len(content),
-            )
-            return content, checksum
+                logger.debug(
+                    "File read completed",
+                    path=str(full_path),
+                    checksum=checksum,
+                    content_length=len(content),
+                )
+                return content, checksum
 
         except Exception as e:
             logger.exception("File read error", path=str(full_path), error=str(e))

src/basic_memory/services/link_resolver.py

@@ -47,6 +47,7 @@ class LinkResolver:
         use_search: bool = True,
         strict: bool = False,
         source_path: Optional[str] = None,
+        load_relations: bool = True,
     ) -> Optional[Entity]:
         """Resolve a markdown link to a permalink.
 
@@ -56,6 +57,7 @@ class LinkResolver:
             strict: If True, only exact matches are allowed (no fuzzy search fallback)
             source_path: Optional path of the source file containing the link.
                         Used to prefer notes closer to the source (context-aware resolution).
+            load_relations: When False, skip eager loading and return a lightweight entity row.
         """
         logger.trace(f"Resolving link: {link_text} (source: {source_path})")
 
@@ -98,6 +100,7 @@ class LinkResolver:
                 strict=strict,
                 source_path=None,
                 project_permalink=project.permalink,
+                load_relations=load_relations,
             )
 
         current_project_permalink = await self._get_current_project_permalink()
@@ -109,6 +112,7 @@ class LinkResolver:
             strict=strict,
             source_path=source_path,
             project_permalink=current_project_permalink,
+            load_relations=load_relations,
         )
         if resolved:
             return resolved
@@ -136,6 +140,7 @@ class LinkResolver:
             strict=strict,
             source_path=None,
             project_permalink=project.permalink,
+            load_relations=load_relations,
         )
 
     def _normalize_link_text(self, link_text: str) -> Tuple[str, Optional[str]]:
@@ -176,6 +181,7 @@ class LinkResolver:
         strict: bool,
         source_path: Optional[str],
         project_permalink: Optional[str],
+        load_relations: bool,
     ) -> Optional[Entity]:
         """Resolve a link within a specific project scope."""
         clean_text = link_text
@@ -223,12 +229,18 @@ class LinkResolver:
                     # Try with .md extension
                     if not relative_path.endswith(".md"):
                         relative_path_md = f"{relative_path}.md"
-                        entity = await entity_repository.get_by_file_path(relative_path_md)
+                        entity = await entity_repository.get_by_file_path(
+                            relative_path_md,
+                            load_relations=load_relations,
+                        )
                         if entity:
                             return entity
 
                     # Try as-is (already has extension or is a permalink)
-                    entity = await entity_repository.get_by_file_path(relative_path)
+                    entity = await entity_repository.get_by_file_path(
+                        relative_path,
+                        load_relations=load_relations,
+                    )
                     if entity:
                         return entity
 
@@ -242,12 +254,18 @@ class LinkResolver:
 
             # Check permalink match
             for candidate_permalink in permalink_candidates:
-                permalink_entity = await entity_repository.get_by_permalink(candidate_permalink)
+                permalink_entity = await entity_repository.get_by_permalink(
+                    candidate_permalink,
+                    load_relations=load_relations,
+                )
                 if permalink_entity and permalink_entity.id not in [c.id for c in candidates]:
                     candidates.append(permalink_entity)
 
             # Check title matches
-            title_entities = await entity_repository.get_by_title(clean_text)
+            title_entities = await entity_repository.get_by_title(
+                clean_text,
+                load_relations=load_relations,
+            )
             for entity in title_entities:
                 # Avoid duplicates (permalink match might also be in title matches)
                 if entity.id not in [c.id for c in candidates]:
@@ -263,13 +281,19 @@ class LinkResolver:
         # Standard resolution (no source context): permalink first, then title
         # 1. Try exact permalink match first (most efficient)
         for candidate_permalink in permalink_candidates:
-            entity = await entity_repository.get_by_permalink(candidate_permalink)
+            entity = await entity_repository.get_by_permalink(
+                candidate_permalink,
+                load_relations=load_relations,
+            )
             if entity:
                 logger.debug(f"Found exact permalink match: {entity.permalink}")
                 return entity
 
         # 2. Try exact title match
-        found = await entity_repository.get_by_title(clean_text)
+        found = await entity_repository.get_by_title(
+            clean_text,
+            load_relations=load_relations,
+        )
         if found:
             # Return first match (shortest path) if no source context
             entity = found[0]
@@ -277,7 +301,10 @@ class LinkResolver:
             return entity
 
         # 3. Try file path
-        found_path = await entity_repository.get_by_file_path(clean_text)
+        found_path = await entity_repository.get_by_file_path(
+            clean_text,
+            load_relations=load_relations,
+        )
         if found_path:
             logger.debug(f"Found entity with path: {found_path.file_path}")
             return found_path
@@ -285,7 +312,10 @@ class LinkResolver:
         # 4. Try file path with .md extension if not already present
         if not clean_text.endswith(".md") and "/" in clean_text:
             file_path_with_md = f"{clean_text}.md"
-            found_path_md = await entity_repository.get_by_file_path(file_path_with_md)
+            found_path_md = await entity_repository.get_by_file_path(
+                file_path_with_md,
+                load_relations=load_relations,
+            )
             if found_path_md:
                 logger.debug(f"Found entity with path (with .md): {found_path_md.file_path}")
                 return found_path_md
@@ -301,13 +331,18 @@ class LinkResolver:
             )
 
             if results:
-                # Look for best match
-                best_match = min(results, key=lambda x: x.score)  # pyright: ignore
+                # Both SQLite and Postgres return results sorted best-first in SQL
+                # (SQLite: ORDER BY score ASC for negative BM25, Postgres: ORDER BY score DESC
+                # for positive ts_rank). Using results[0] is backend-agnostic and correct.
+                best_match = results[0]
                 logger.trace(
                     f"Selected best match from {len(results)} results: {best_match.permalink}"
                 )
                 if best_match.permalink:
-                    return await entity_repository.get_by_permalink(best_match.permalink)
+                    return await entity_repository.get_by_permalink(
+                        best_match.permalink,
+                        load_relations=load_relations,
+                    )
 
         # if we couldn't find anything then return None
         return None

src/basic_memory/services/project_service.py

@@ -11,11 +11,13 @@ from typing import TYPE_CHECKING, Dict, Optional, Sequence
 
 from loguru import logger
 from sqlalchemy import text
+from sqlalchemy.exc import OperationalError as SAOperationalError
 
 from basic_memory.models import Project
 from basic_memory.repository.project_repository import ProjectRepository
 from basic_memory.schemas import (
     ActivityMetrics,
+    EmbeddingStatus,
     ProjectInfoResponse,
     ProjectStatistics,
     SystemStatus,
@@ -81,6 +83,21 @@ class ProjectService:
         """
         return self.config_manager.default_project
 
+    async def get_default_project_name(self) -> str:
+        """Get the default project name, falling back to the database.
+
+        ConfigManager reads from the local config file, which doesn't exist
+        in cloud mode. When it returns None, fall back to the is_default
+        flag stored in the database.
+        """
+        default = self.config_manager.default_project
+        if default is not None:
+            return default
+        db_default = await self.repository.get_default_project()
+        if db_default is not None:
+            return db_default.name
+        raise ValueError("No default project configured")
+
     @property
     def current_project(self) -> Optional[str]:
         """Get the name of the currently active project.
@@ -597,6 +614,9 @@ class ProjectService:
         # Get activity metrics for the specified project
         activity = await self.get_activity_metrics(db_project.id)
 
+        # Get embedding status for the specified project
+        embedding_status = await self.get_embedding_status(db_project.id)
+
         # Get system status
         system = self.get_system_status()
 
@@ -650,6 +670,7 @@ class ProjectService:
             statistics=statistics,
             activity=activity,
             system=system,
+            embedding_status=embedding_status,
         )
 
     async def get_statistics(self, project_id: int) -> ProjectStatistics:
@@ -918,6 +939,193 @@ class ProjectService:
             monthly_growth=monthly_growth,
         )
 
+    async def get_embedding_status(self, project_id: int) -> EmbeddingStatus:
+        """Get embedding/vector index status for the specified project.
+
+        Reports config, counts, and whether a reindex is recommended.
+        """
+        config = self.config_manager.config
+        semantic_enabled = config.semantic_search_enabled
+
+        # When semantic search is disabled, return minimal status
+        if not semantic_enabled:
+            return EmbeddingStatus(semantic_search_enabled=False)
+
+        provider = config.semantic_embedding_provider
+        model = config.semantic_embedding_model
+        dimensions = config.semantic_embedding_dimensions
+
+        is_postgres = config.database_backend == DatabaseBackend.POSTGRES
+
+        # --- Check vector table existence ---
+        # Both search_vector_chunks and search_vector_embeddings must exist
+        # for the detailed stats queries (JOINs between them) to work.
+        if is_postgres:
+            table_check_sql = text(
+                "SELECT COUNT(*) FROM information_schema.tables "
+                "WHERE table_name IN ('search_vector_chunks', 'search_vector_embeddings')"
+            )
+        else:
+            table_check_sql = text(
+                "SELECT COUNT(*) FROM sqlite_master "
+                "WHERE type = 'table' AND name IN ('search_vector_chunks', 'search_vector_embeddings')"
+            )
+
+        table_result = await self.repository.execute_query(table_check_sql, {})
+        vector_tables_exist = (table_result.scalar() or 0) == 2
+
+        if not vector_tables_exist:
+            # Count distinct entities in search index for the recommendation message
+            si_result = await self.repository.execute_query(
+                text(
+                    "SELECT COUNT(DISTINCT entity_id) FROM search_index "
+                    "WHERE project_id = :project_id"
+                ),
+                {"project_id": project_id},
+            )
+            total_indexed_entities = si_result.scalar() or 0
+
+            return EmbeddingStatus(
+                semantic_search_enabled=True,
+                embedding_provider=provider,
+                embedding_model=model,
+                embedding_dimensions=dimensions,
+                total_indexed_entities=total_indexed_entities,
+                vector_tables_exist=False,
+                reindex_recommended=True,
+                reindex_reason=("Vector tables not initialized — run: bm reindex --embeddings"),
+            )
+
+        # --- Count queries (tables exist) ---
+        # Filter by entity existence to exclude stale rows from deleted entities
+        # that remain in derived search tables (search_index, search_vector_chunks)
+        entity_exists = "AND entity_id IN (SELECT id FROM entity WHERE project_id = :project_id)"
+        # Same filter for aliased chunks table (used in JOIN queries below)
+        chunk_entity_exists = (
+            "AND c.entity_id IN (SELECT id FROM entity WHERE project_id = :project_id)"
+        )
+
+        si_result = await self.repository.execute_query(
+            text(
+                "SELECT COUNT(DISTINCT entity_id) FROM search_index "
+                f"WHERE project_id = :project_id {entity_exists}"
+            ),
+            {"project_id": project_id},
+        )
+        total_indexed_entities = si_result.scalar() or 0
+
+        try:
+            chunks_result = await self.repository.execute_query(
+                text(
+                    "SELECT COUNT(*) FROM search_vector_chunks "
+                    f"WHERE project_id = :project_id {entity_exists}"
+                ),
+                {"project_id": project_id},
+            )
+            total_chunks = chunks_result.scalar() or 0
+
+            entities_with_chunks_result = await self.repository.execute_query(
+                text(
+                    "SELECT COUNT(DISTINCT entity_id) FROM search_vector_chunks "
+                    f"WHERE project_id = :project_id {entity_exists}"
+                ),
+                {"project_id": project_id},
+            )
+            total_entities_with_chunks = entities_with_chunks_result.scalar() or 0
+
+            # Embeddings count — join pattern differs between SQLite and Postgres
+            if is_postgres:
+                embeddings_sql = text(
+                    "SELECT COUNT(*) FROM search_vector_chunks c "
+                    "JOIN search_vector_embeddings e ON e.chunk_id = c.id "
+                    f"WHERE c.project_id = :project_id {chunk_entity_exists}"
+                )
+            else:
+                embeddings_sql = text(
+                    "SELECT COUNT(*) FROM search_vector_chunks c "
+                    "JOIN search_vector_embeddings e ON e.rowid = c.id "
+                    f"WHERE c.project_id = :project_id {chunk_entity_exists}"
+                )
+
+            embeddings_result = await self.repository.execute_query(
+                embeddings_sql, {"project_id": project_id}
+            )
+            total_embeddings = embeddings_result.scalar() or 0
+
+            # Orphaned chunks (chunks without embeddings — indicates interrupted indexing)
+            if is_postgres:
+                orphan_sql = text(
+                    "SELECT COUNT(*) FROM search_vector_chunks c "
+                    "LEFT JOIN search_vector_embeddings e ON e.chunk_id = c.id "
+                    f"WHERE c.project_id = :project_id AND e.chunk_id IS NULL {chunk_entity_exists}"
+                )
+            else:
+                orphan_sql = text(
+                    "SELECT COUNT(*) FROM search_vector_chunks c "
+                    "LEFT JOIN search_vector_embeddings e ON e.rowid = c.id "
+                    f"WHERE c.project_id = :project_id AND e.rowid IS NULL {chunk_entity_exists}"
+                )
+
+            orphan_result = await self.repository.execute_query(
+                orphan_sql, {"project_id": project_id}
+            )
+            orphaned_chunks = orphan_result.scalar() or 0
+        except SAOperationalError as exc:
+            # Trigger: sqlite_master can list vec0 virtual tables even when sqlite-vec
+            # is not loaded in the current Python runtime.
+            # Why: project info should degrade gracefully instead of crashing on stats queries.
+            # Outcome: report vector tables as unavailable and point the user to install the
+            # missing dependency before rebuilding embeddings.
+            if is_postgres or "no such module: vec0" not in str(exc).lower():
+                raise
+
+            return EmbeddingStatus(
+                semantic_search_enabled=True,
+                embedding_provider=provider,
+                embedding_model=model,
+                embedding_dimensions=dimensions,
+                total_indexed_entities=total_indexed_entities,
+                vector_tables_exist=False,
+                reindex_recommended=True,
+                reindex_reason=(
+                    "SQLite vector tables exist but sqlite-vec is unavailable in this Python "
+                    "environment — install/update basic-memory, then run: bm reindex --embeddings"
+                ),
+            )
+
+        # --- Reindex recommendation logic (priority order) ---
+        reindex_recommended = False
+        reindex_reason = None
+
+        if total_indexed_entities > 0 and total_chunks == 0:
+            reindex_recommended = True
+            reindex_reason = "Embeddings have never been built — run: bm reindex --embeddings"
+        elif orphaned_chunks > 0:
+            reindex_recommended = True
+            reindex_reason = (
+                f"{orphaned_chunks} orphaned chunks found (interrupted indexing) "
+                "— run: bm reindex --embeddings"
+            )
+        elif total_indexed_entities > total_entities_with_chunks:
+            missing = total_indexed_entities - total_entities_with_chunks
+            reindex_recommended = True
+            reindex_reason = f"{missing} entities missing embeddings — run: bm reindex --embeddings"
+
+        return EmbeddingStatus(
+            semantic_search_enabled=True,
+            embedding_provider=provider,
+            embedding_model=model,
+            embedding_dimensions=dimensions,
+            total_indexed_entities=total_indexed_entities,
+            total_entities_with_chunks=total_entities_with_chunks,
+            total_chunks=total_chunks,
+            total_embeddings=total_embeddings,
+            orphaned_chunks=orphaned_chunks,
+            vector_tables_exist=True,
+            reindex_recommended=reindex_recommended,
+            reindex_reason=reindex_reason,
+        )
+
     def get_system_status(self) -> SystemStatus:
         """Get system status information."""
         import basic_memory

src/basic_memory/services/search_service.py

@@ -5,15 +5,19 @@ import re
 from datetime import datetime
 from typing import List, Optional, Set, Dict, Any
 
-
 from dateparser import parse
 from fastapi import BackgroundTasks
 from loguru import logger
 from sqlalchemy import text
 
+from basic_memory import telemetry
 from basic_memory.models import Entity
 from basic_memory.repository import EntityRepository
-from basic_memory.repository.search_repository import SearchRepository, SearchIndexRow
+from basic_memory.repository.search_repository import (
+    SearchIndexRow,
+    SearchRepository,
+    VectorSyncBatchResult,
+)
 from basic_memory.schemas.search import SearchQuery, SearchItemType, SearchRetrievalMode
 from basic_memory.services import FileService
 
@@ -148,8 +152,6 @@ class SearchService:
             logger.debug("no criteria passed to query")
             return []
 
-        logger.trace(f"Searching with query: {query}")
-
         after_date = (
             (
                 query.after_date
@@ -171,22 +173,49 @@ class SearchService:
 
         retrieval_mode = query.retrieval_mode or SearchRetrievalMode.FTS
         strict_search_text = query.text
+        has_query = bool(
+            strict_search_text or query.title or query.permalink or query.permalink_match
+        )
+        has_filters = bool(
+            metadata_filters
+            or query.note_types
+            or query.entity_types
+            or after_date
+            or query.tags
+            or query.status
+        )
 
-        # First pass: preserve existing strict search behavior.
-        results = await self.repository.search(
-            search_text=strict_search_text,
-            permalink=query.permalink,
-            permalink_match=query.permalink_match,
-            title=query.title,
-            note_types=query.note_types,
-            search_item_types=query.entity_types,
-            after_date=after_date,
-            metadata_filters=metadata_filters,
-            retrieval_mode=retrieval_mode,
-            min_similarity=query.min_similarity,
+        with telemetry.scope(
+            "search.execute",
+            retrieval_mode=retrieval_mode.value,
+            has_query=has_query,
+            has_filters=has_filters,
             limit=limit,
             offset=offset,
-        )
+        ):
+            logger.trace(f"Searching with query: {query}")
+            with telemetry.scope(
+                "search.repository_query",
+                retrieval_mode=retrieval_mode.value,
+                phase="repository_query",
+                has_query=has_query,
+                has_filters=has_filters,
+            ):
+                # First pass: preserve existing strict search behavior.
+                results = await self.repository.search(
+                    search_text=strict_search_text,
+                    permalink=query.permalink,
+                    permalink_match=query.permalink_match,
+                    title=query.title,
+                    note_types=query.note_types,
+                    search_item_types=query.entity_types,
+                    after_date=after_date,
+                    metadata_filters=metadata_filters,
+                    retrieval_mode=retrieval_mode,
+                    min_similarity=query.min_similarity,
+                    limit=limit,
+                    offset=offset,
+                )
 
         # Trigger: strict FTS with plain multi-term text returned no results.
         # Why: natural-language queries often include stopwords that over-constrain implicit AND.
@@ -205,20 +234,34 @@ class SearchService:
             "Strict FTS returned 0 results; retrying relaxed FTS query "
             f"strict='{strict_search_text}' relaxed='{relaxed_search_text}'"
         )
-        return await self.repository.search(
-            search_text=relaxed_search_text,
-            permalink=query.permalink,
-            permalink_match=query.permalink_match,
-            title=query.title,
-            note_types=query.note_types,
-            search_item_types=query.entity_types,
-            after_date=after_date,
-            metadata_filters=metadata_filters,
-            retrieval_mode=retrieval_mode,
-            min_similarity=query.min_similarity,
+        with telemetry.scope(
+            "search.relaxed_fts_retry",
+            retrieval_mode=retrieval_mode.value,
+            token_count=len(self._tokenize_fts_text(strict_search_text)),
             limit=limit,
             offset=offset,
-        )
+        ):
+            with telemetry.scope(
+                "search.repository_query",
+                retrieval_mode=retrieval_mode.value,
+                phase="repository_query",
+                has_query=has_query,
+                has_filters=has_filters,
+            ):
+                return await self.repository.search(
+                    search_text=relaxed_search_text,
+                    permalink=query.permalink,
+                    permalink_match=query.permalink_match,
+                    title=query.title,
+                    note_types=query.note_types,
+                    search_item_types=query.entity_types,
+                    after_date=after_date,
+                    metadata_filters=metadata_filters,
+                    retrieval_mode=retrieval_mode,
+                    min_similarity=query.min_similarity,
+                    limit=limit,
+                    offset=offset,
+                )
 
     @staticmethod
     def _tokenize_fts_text(search_text: str) -> list[str]:
@@ -347,20 +390,29 @@ class SearchService:
         entity: Entity,
         content: str | None = None,
     ) -> None:
-        logger.info(
+        logger.debug(
             f"[BackgroundTask] Starting search index for entity_id={entity.id} "
             f"permalink={entity.permalink} project_id={entity.project_id}"
         )
         try:
-            # delete all search index data associated with entity
-            await self.repository.delete_by_entity_id(entity_id=entity.id)
+            with telemetry.scope(
+                "search.index_entity_data",
+                phase="index_entity_data",
+                result_count=1,
+            ):
+                with telemetry.scope(
+                    "search.index.delete_existing",
+                    phase="delete_existing",
+                    result_count=1,
+                ):
+                    await self.repository.delete_by_entity_id(entity_id=entity.id)
 
-            # reindex
-            await self.index_entity_markdown(
-                entity, content
-            ) if entity.is_markdown else await self.index_entity_file(entity)
+                if entity.is_markdown:
+                    await self.index_entity_markdown(entity, content)
+                else:
+                    await self.index_entity_file(entity)
 
-            logger.info(
+            logger.debug(
                 f"[BackgroundTask] Completed search index for entity_id={entity.id} "
                 f"permalink={entity.permalink}"
             )
@@ -377,6 +429,17 @@ class SearchService:
         """Refresh vector chunks for one entity in repositories that support semantic indexing."""
         await self.repository.sync_entity_vectors(entity_id)
 
+    async def sync_entity_vectors_batch(
+        self,
+        entity_ids: list[int],
+        progress_callback=None,
+    ) -> VectorSyncBatchResult:
+        """Refresh vector chunks for a batch of entities."""
+        return await self.repository.sync_entity_vectors_batch(
+            entity_ids,
+            progress_callback=progress_callback,
+        )
+
     async def reindex_vectors(self, progress_callback=None) -> dict:
         """Rebuild vector embeddings for all entities.
 
@@ -387,41 +450,100 @@ class SearchService:
             dict with stats: total_entities, embedded, skipped, errors
         """
         entities = await self.entity_repository.find_all()
-        stats = {"total_entities": len(entities), "embedded": 0, "skipped": 0, "errors": 0}
+        entity_ids = [entity.id for entity in entities]
 
-        for i, entity in enumerate(entities):
-            if progress_callback:
-                progress_callback(entity.id, i, len(entities))
-            try:
-                await self.repository.sync_entity_vectors(entity.id)
-                stats["embedded"] += 1
-            except Exception as e:
-                logger.warning(f"Failed to embed entity {entity.id} ({entity.permalink}): {e}")
-                stats["errors"] += 1
+        # Clean up stale rows in search_index and search_vector_chunks
+        # that reference entity_ids no longer in the entity table
+        await self._purge_stale_search_rows()
+
+        batch_result = await self.repository.sync_entity_vectors_batch(
+            entity_ids,
+            progress_callback=progress_callback,
+        )
+        stats = {
+            "total_entities": batch_result.entities_total,
+            "embedded": batch_result.entities_synced,
+            "skipped": 0,
+            "errors": batch_result.entities_failed,
+        }
+
+        for failed_entity_id in batch_result.failed_entity_ids:
+            logger.warning(f"Failed to embed entity {failed_entity_id}")
 
         return stats
 
+    async def _purge_stale_search_rows(self) -> None:
+        """Remove rows from search_index and search_vector_chunks for deleted entities.
+
+        Trigger: entities are deleted but their derived search rows remain
+        Why: stale rows inflate embedding coverage stats in project info
+        Outcome: search tables only contain rows for entities that still exist
+        """
+        from basic_memory.repository.sqlite_search_repository import SQLiteSearchRepository
+        from sqlalchemy import text
+
+        project_id = self.repository.project_id
+        stale_entity_filter = (
+            "entity_id NOT IN (SELECT id FROM entity WHERE project_id = :project_id)"
+        )
+        params = {"project_id": project_id}
+
+        # Delete stale search_index rows
+        await self.repository.execute_query(
+            text(
+                f"DELETE FROM search_index WHERE project_id = :project_id AND {stale_entity_filter}"
+            ),
+            params,
+        )
+
+        # SQLite vec has no CASCADE — must delete embeddings before chunks
+        if isinstance(self.repository, SQLiteSearchRepository):
+            await self.repository.execute_query(
+                text(
+                    "DELETE FROM search_vector_embeddings WHERE rowid IN ("
+                    "SELECT id FROM search_vector_chunks "
+                    f"WHERE project_id = :project_id AND {stale_entity_filter})"
+                ),
+                params,
+            )
+
+        # Postgres CASCADE handles embedding deletion automatically
+        await self.repository.execute_query(
+            text(
+                f"DELETE FROM search_vector_chunks "
+                f"WHERE project_id = :project_id AND {stale_entity_filter}"
+            ),
+            params,
+        )
+
+        logger.info("Purged stale search rows for deleted entities", project_id=project_id)
+
     async def index_entity_file(
         self,
         entity: Entity,
     ) -> None:
-        # Index entity file with no content
-        await self.repository.index_item(
-            SearchIndexRow(
-                id=entity.id,
-                entity_id=entity.id,
-                type=SearchItemType.ENTITY.value,
-                title=_strip_nul(entity.title),
-                permalink=entity.permalink,  # Required for Postgres NOT NULL constraint
-                file_path=entity.file_path,
-                metadata={
-                    "note_type": entity.note_type,
-                },
-                created_at=entity.created_at,
-                updated_at=_mtime_to_datetime(entity),
-                project_id=entity.project_id,
+        with telemetry.scope(
+            "search.index_file",
+            phase="index_file",
+            result_count=1,
+        ):
+            # Index entity file with no content
+            await self.repository.index_item(
+                SearchIndexRow(
+                    id=entity.id,
+                    entity_id=entity.id,
+                    type=SearchItemType.ENTITY.value,
+                    title=_strip_nul(entity.title),
+                    permalink=entity.permalink,  # Required for Postgres NOT NULL constraint
+                    file_path=entity.file_path,
+                    metadata={
+                        "note_type": entity.note_type,
+                    },
+                    created_at=entity.created_at,
+                    updated_at=_mtime_to_datetime(entity),
+                    project_id=entity.project_id,
+                )
             )
-        )
 
     async def index_entity_markdown(
         self,
@@ -454,129 +576,144 @@ class SearchService:
         The project_id is automatically added by the repository when indexing.
         """
 
-        # Collect all search index rows to batch insert at the end
-        rows_to_index = []
+        with telemetry.scope(
+            "search.index_markdown",
+            phase="index_markdown",
+            result_count=1,
+        ):
+            rows_to_index = []
 
-        content_stems = []
-        content_snippet = ""
-        title_variants = self._generate_variants(entity.title)
-        content_stems.extend(title_variants)
+            content_stems = []
+            content_snippet = ""
+            title_variants = self._generate_variants(entity.title)
+            content_stems.extend(title_variants)
 
-        # Use provided content or read from file
-        if content is None:
-            content = await self.file_service.read_entity_content(entity)
-        if content:
-            content_stems.append(content)
-            # Store full content for vector embedding quality.
-            # The chunker in the vector pipeline splits this into
-            # appropriately-sized pieces for embedding.
-            content_snippet = _strip_nul(content)
+            if content is None:
+                with telemetry.scope(
+                    "search.index.read_content",
+                    phase="read_content",
+                    result_count=1,
+                ):
+                    content = await self.file_service.read_entity_content(entity)
+            if content:
+                content_stems.append(content)
+                content_snippet = _strip_nul(content)
 
-        if entity.permalink:
-            content_stems.extend(self._generate_variants(entity.permalink))
+            with telemetry.scope(
+                "search.index.build_rows",
+                phase="build_rows",
+                result_count=1,
+            ):
+                if entity.permalink:
+                    content_stems.extend(self._generate_variants(entity.permalink))
 
-        content_stems.extend(self._generate_variants(entity.file_path))
+                content_stems.extend(self._generate_variants(entity.file_path))
 
-        # Add entity tags from frontmatter to search content
-        entity_tags = self._extract_entity_tags(entity)
-        if entity_tags:
-            content_stems.extend(entity_tags)
+                entity_tags = self._extract_entity_tags(entity)
+                if entity_tags:
+                    content_stems.extend(entity_tags)
 
-        entity_content_stems = _strip_nul("\n".join(p for p in content_stems if p and p.strip()))
-
-        # Truncate to stay under Postgres's 8KB index row limit
-        if len(entity_content_stems) > MAX_CONTENT_STEMS_SIZE:  # pragma: no cover
-            entity_content_stems = entity_content_stems[:MAX_CONTENT_STEMS_SIZE]  # pragma: no cover
-
-        # Add entity row
-        rows_to_index.append(
-            SearchIndexRow(
-                id=entity.id,
-                type=SearchItemType.ENTITY.value,
-                title=_strip_nul(entity.title),
-                content_stems=entity_content_stems,
-                content_snippet=content_snippet,
-                permalink=entity.permalink,
-                file_path=entity.file_path,
-                entity_id=entity.id,
-                metadata={
-                    "note_type": entity.note_type,
-                },
-                created_at=entity.created_at,
-                updated_at=_mtime_to_datetime(entity),
-                project_id=entity.project_id,
-            )
-        )
-
-        # Add observation rows - dedupe by permalink to avoid unique constraint violations
-        # Two observations with same entity/category/content generate identical permalinks
-        seen_permalinks: set[str] = {entity.permalink} if entity.permalink else set()
-        for obs in entity.observations:
-            obs_permalink = obs.permalink
-            if obs_permalink in seen_permalinks:
-                logger.debug(f"Skipping duplicate observation permalink: {obs_permalink}")
-                continue
-            seen_permalinks.add(obs_permalink)
-
-            # Index with parent entity's file path since that's where it's defined
-            obs_content_stems = _strip_nul(
-                "\n".join(p for p in self._generate_variants(obs.content) if p and p.strip())
-            )
-            # Truncate to stay under Postgres's 8KB index row limit
-            if len(obs_content_stems) > MAX_CONTENT_STEMS_SIZE:  # pragma: no cover
-                obs_content_stems = obs_content_stems[:MAX_CONTENT_STEMS_SIZE]  # pragma: no cover
-            rows_to_index.append(
-                SearchIndexRow(
-                    id=obs.id,
-                    type=SearchItemType.OBSERVATION.value,
-                    title=_strip_nul(f"{obs.category}: {obs.content[:100]}..."),
-                    content_stems=obs_content_stems,
-                    content_snippet=_strip_nul(obs.content),
-                    permalink=obs_permalink,
-                    file_path=entity.file_path,
-                    category=obs.category,
-                    entity_id=entity.id,
-                    metadata={
-                        "tags": obs.tags,
-                    },
-                    created_at=entity.created_at,
-                    updated_at=_mtime_to_datetime(entity),
-                    project_id=entity.project_id,
+                entity_content_stems = _strip_nul(
+                    "\n".join(p for p in content_stems if p and p.strip())
                 )
-            )
 
-        # Add relation rows (only outgoing relations defined in this file)
-        for rel in entity.outgoing_relations:
-            # Create descriptive title showing the relationship
-            relation_title = _strip_nul(
-                f"{rel.from_entity.title} → {rel.to_entity.title}"
-                if rel.to_entity
-                else f"{rel.from_entity.title}"
-            )
+                if len(entity_content_stems) > MAX_CONTENT_STEMS_SIZE:  # pragma: no cover
+                    entity_content_stems = entity_content_stems[
+                        :MAX_CONTENT_STEMS_SIZE
+                    ]  # pragma: no cover
 
-            rel_content_stems = _strip_nul(
-                "\n".join(p for p in self._generate_variants(relation_title) if p and p.strip())
-            )
-            rows_to_index.append(
-                SearchIndexRow(
-                    id=rel.id,
-                    title=relation_title,
-                    permalink=rel.permalink,
-                    content_stems=rel_content_stems,
-                    file_path=entity.file_path,
-                    type=SearchItemType.RELATION.value,
-                    entity_id=entity.id,
-                    from_id=rel.from_id,
-                    to_id=rel.to_id,
-                    relation_type=rel.relation_type,
-                    created_at=entity.created_at,
-                    updated_at=_mtime_to_datetime(entity),
-                    project_id=entity.project_id,
+                rows_to_index.append(
+                    SearchIndexRow(
+                        id=entity.id,
+                        type=SearchItemType.ENTITY.value,
+                        title=_strip_nul(entity.title),
+                        content_stems=entity_content_stems,
+                        content_snippet=content_snippet,
+                        permalink=entity.permalink,
+                        file_path=entity.file_path,
+                        entity_id=entity.id,
+                        metadata={
+                            "note_type": entity.note_type,
+                        },
+                        created_at=entity.created_at,
+                        updated_at=_mtime_to_datetime(entity),
+                        project_id=entity.project_id,
+                    )
                 )
-            )
 
-        # Batch insert all rows at once
-        await self.repository.bulk_index_items(rows_to_index)
+                seen_permalinks: set[str] = {entity.permalink} if entity.permalink else set()
+                for obs in entity.observations:
+                    obs_permalink = obs.permalink
+                    if obs_permalink in seen_permalinks:
+                        logger.debug(f"Skipping duplicate observation permalink: {obs_permalink}")
+                        continue
+                    seen_permalinks.add(obs_permalink)
+
+                    obs_content_stems = _strip_nul(
+                        "\n".join(
+                            p for p in self._generate_variants(obs.content) if p and p.strip()
+                        )
+                    )
+                    if len(obs_content_stems) > MAX_CONTENT_STEMS_SIZE:  # pragma: no cover
+                        obs_content_stems = obs_content_stems[
+                            :MAX_CONTENT_STEMS_SIZE
+                        ]  # pragma: no cover
+                    rows_to_index.append(
+                        SearchIndexRow(
+                            id=obs.id,
+                            type=SearchItemType.OBSERVATION.value,
+                            title=_strip_nul(f"{obs.category}: {obs.content[:100]}..."),
+                            content_stems=obs_content_stems,
+                            content_snippet=_strip_nul(obs.content),
+                            permalink=obs_permalink,
+                            file_path=entity.file_path,
+                            category=obs.category,
+                            entity_id=entity.id,
+                            metadata={
+                                "tags": obs.tags,
+                            },
+                            created_at=entity.created_at,
+                            updated_at=_mtime_to_datetime(entity),
+                            project_id=entity.project_id,
+                        )
+                    )
+
+                for rel in entity.outgoing_relations:
+                    relation_title = _strip_nul(
+                        f"{rel.from_entity.title} -> {rel.to_entity.title}"
+                        if rel.to_entity
+                        else f"{rel.from_entity.title}"
+                    )
+
+                    rel_content_stems = _strip_nul(
+                        "\n".join(
+                            p for p in self._generate_variants(relation_title) if p and p.strip()
+                        )
+                    )
+                    rows_to_index.append(
+                        SearchIndexRow(
+                            id=rel.id,
+                            title=relation_title,
+                            permalink=rel.permalink,
+                            content_stems=rel_content_stems,
+                            file_path=entity.file_path,
+                            type=SearchItemType.RELATION.value,
+                            entity_id=entity.id,
+                            from_id=rel.from_id,
+                            to_id=rel.to_id,
+                            relation_type=rel.relation_type,
+                            created_at=entity.created_at,
+                            updated_at=_mtime_to_datetime(entity),
+                            project_id=entity.project_id,
+                        )
+                    )
+
+            with telemetry.scope(
+                "search.index.bulk_upsert",
+                phase="bulk_upsert",
+                result_count=len(rows_to_index),
+            ):
+                await self.repository.bulk_index_items(rows_to_index)
 
     async def delete_by_permalink(self, permalink: str):
         """Delete an item from the search index."""

src/basic_memory/sync/sync_service.py

@@ -15,6 +15,7 @@ import aiofiles.os
 from loguru import logger
 from sqlalchemy.exc import IntegrityError
 
+from basic_memory import telemetry
 from basic_memory import db
 from basic_memory.config import BasicMemoryConfig, ConfigManager
 from basic_memory.file_utils import has_frontmatter
@@ -36,6 +37,7 @@ from basic_memory.services.search_service import SearchService
 
 # Circuit breaker configuration
 MAX_CONSECUTIVE_FAILURES = 3
+SLOW_FILE_SYNC_WARNING_MS = 500
 
 
 @dataclass
@@ -265,112 +267,163 @@ class SyncService:
 
         start_time = time.time()
         sync_start_timestamp = time.time()  # Capture at start for watermark
-        logger.info(f"Sync operation started for directory: {directory} (force_full={force_full})")
-
-        # initial paths from db to sync
-        # path -> checksum
-        report = await self.scan(directory, force_full=force_full)
-
-        # order of sync matters to resolve relations effectively
-        logger.info(
-            f"Sync changes detected: new_files={len(report.new)}, modified_files={len(report.modified)}, "
-            + f"deleted_files={len(report.deleted)}, moved_files={len(report.moves)}"
-        )
-
-        # sync moves first
-        for old_path, new_path in report.moves.items():
-            # in the case where a file has been deleted and replaced by another file
-            # it will show up in the move and modified lists, so handle it in modified
-            if new_path in report.modified:
-                report.modified.remove(new_path)
-                logger.debug(
-                    f"File marked as moved and modified: old_path={old_path}, new_path={new_path}"
-                )
-            else:
-                await self.handle_move(old_path, new_path)
-
-        # deleted next
-        for path in report.deleted:
-            await self.handle_delete(path)
-
-        # then new and modified
-        for path in report.new:
-            entity, _ = await self.sync_file(path, new=True)
-
-            # Track if file was skipped
-            if entity is None and await self._should_skip_file(path):
-                failure_info = self._file_failures[path]
-                report.skipped_files.append(
-                    SkippedFile(
-                        path=path,
-                        reason=failure_info.last_error,
-                        failure_count=failure_info.count,
-                        first_failed=failure_info.first_failure,
-                    )
-                )
-
-        for path in report.modified:
-            entity, _ = await self.sync_file(path, new=False)
-
-            # Track if file was skipped
-            if entity is None and await self._should_skip_file(path):
-                failure_info = self._file_failures[path]
-                report.skipped_files.append(
-                    SkippedFile(
-                        path=path,
-                        reason=failure_info.last_error,
-                        failure_count=failure_info.count,
-                        first_failed=failure_info.first_failure,
-                    )
-                )
-
-        # Only resolve relations if there were actual changes
-        # If no files changed, no new unresolved relations could have been created
-        if report.total > 0:
-            await self.resolve_relations()
-        else:
-            logger.info("Skipping relation resolution - no file changes detected")
-
-        # Update scan watermark after successful sync
-        # Use the timestamp from sync start (not end) to ensure we catch files
-        # created during the sync on the next iteration
-        current_file_count = await self._quick_count_files(directory)
-        if self.entity_repository.project_id is not None:
-            project = await self.project_repository.find_by_id(self.entity_repository.project_id)
-            if project:
-                await self.project_repository.update(
-                    project.id,
-                    {
-                        "last_scan_timestamp": sync_start_timestamp,
-                        "last_file_count": current_file_count,
-                    },
-                )
-                logger.debug(
-                    f"Updated scan watermark: timestamp={sync_start_timestamp}, "
-                    f"file_count={current_file_count}"
-                )
-
-        duration_ms = int((time.time() - start_time) * 1000)
-
-        # Log summary with skipped files if any
-        if report.skipped_files:
-            logger.warning(
-                f"Sync completed with {len(report.skipped_files)} skipped files: "
-                f"directory={directory}, total_changes={report.total}, "
-                f"skipped={len(report.skipped_files)}, duration_ms={duration_ms}"
-            )
-            for skipped in report.skipped_files:
-                logger.warning(
-                    f"Skipped file: path={skipped.path}, "
-                    f"failures={skipped.failure_count}, reason={skipped.reason}"
-                )
-        else:
+        with telemetry.operation(
+            "sync.project.run",
+            project_name=project_name,
+            force_full=force_full,
+        ):
             logger.info(
-                f"Sync operation completed: directory={directory}, "
-                f"total_changes={report.total}, duration_ms={duration_ms}"
+                f"Sync operation started for directory: {directory} (force_full={force_full})"
             )
 
-        return report
+            # initial paths from db to sync
+            # path -> checksum
+            with telemetry.scope("sync.project.scan", force_full=force_full):
+                report = await self.scan(directory, force_full=force_full)
+
+            # order of sync matters to resolve relations effectively
+            logger.info(
+                f"Sync changes detected: new_files={len(report.new)}, modified_files={len(report.modified)}, "
+                + f"deleted_files={len(report.deleted)}, moved_files={len(report.moves)}"
+            )
+
+            with telemetry.scope(
+                "sync.project.apply_changes",
+                new_count=len(report.new),
+                modified_count=len(report.modified),
+                deleted_count=len(report.deleted),
+                move_count=len(report.moves),
+            ):
+                # sync moves first
+                for old_path, new_path in report.moves.items():
+                    # in the case where a file has been deleted and replaced by another file
+                    # it will show up in the move and modified lists, so handle it in modified
+                    if new_path in report.modified:
+                        report.modified.remove(new_path)
+                        logger.debug(
+                            f"File marked as moved and modified: old_path={old_path}, new_path={new_path}"
+                        )
+                    else:
+                        await self.handle_move(old_path, new_path)
+
+                # deleted next
+                for path in report.deleted:
+                    await self.handle_delete(path)
+
+                # then new and modified — collect entity IDs for batch vector embedding
+                synced_entity_ids: list[int] = []
+
+                for path in report.new:
+                    entity, _ = await self.sync_file(path, new=True)
+
+                    if entity is not None:
+                        synced_entity_ids.append(entity.id)
+                    # Track if file was skipped
+                    elif await self._should_skip_file(path):
+                        failure_info = self._file_failures[path]
+                        report.skipped_files.append(
+                            SkippedFile(
+                                path=path,
+                                reason=failure_info.last_error,
+                                failure_count=failure_info.count,
+                                first_failed=failure_info.first_failure,
+                            )
+                        )
+
+                for path in report.modified:
+                    entity, _ = await self.sync_file(path, new=False)
+
+                    if entity is not None:
+                        synced_entity_ids.append(entity.id)
+                    # Track if file was skipped
+                    elif await self._should_skip_file(path):
+                        failure_info = self._file_failures[path]
+                        report.skipped_files.append(
+                            SkippedFile(
+                                path=path,
+                                reason=failure_info.last_error,
+                                failure_count=failure_info.count,
+                                first_failed=failure_info.first_failure,
+                            )
+                        )
+
+            # Only resolve relations if there were actual changes
+            # If no files changed, no new unresolved relations could have been created
+            if report.total > 0:
+                with telemetry.scope(
+                    "sync.project.resolve_relations", relation_scope="all_pending"
+                ):
+                    await self.resolve_relations()
+            else:
+                logger.info("Skipping relation resolution - no file changes detected")
+
+            # Batch-generate vector embeddings for all synced entities
+            if synced_entity_ids and self.app_config.semantic_search_enabled:
+                try:
+                    with telemetry.scope(
+                        "sync.project.sync_embeddings",
+                        entity_count=len(synced_entity_ids),
+                    ):
+                        logger.info(
+                            f"Generating semantic embeddings for {len(synced_entity_ids)} entities..."
+                        )
+                        batch_result = await self.search_service.sync_entity_vectors_batch(
+                            synced_entity_ids
+                        )
+                        logger.info(
+                            f"Semantic embeddings complete: "
+                            f"synced={batch_result.entities_synced}, "
+                            f"failed={batch_result.entities_failed}"
+                        )
+                except SemanticDependenciesMissingError:
+                    logger.warning(
+                        "Semantic search dependencies missing — vector embeddings skipped. "
+                        "Run 'bm reindex --embeddings' after resolving the dependency issue."
+                    )
+
+            # Update scan watermark after successful sync
+            # Use the timestamp from sync start (not end) to ensure we catch files
+            # created during the sync on the next iteration
+            with telemetry.scope("sync.project.update_watermark"):
+                current_file_count = await self._quick_count_files(directory)
+                if self.entity_repository.project_id is not None:
+                    project = await self.project_repository.find_by_id(
+                        self.entity_repository.project_id
+                    )
+                    if project:
+                        await self.project_repository.update(
+                            project.id,
+                            {
+                                "last_scan_timestamp": sync_start_timestamp,
+                                "last_file_count": current_file_count,
+                            },
+                        )
+                        logger.debug(
+                            f"Updated scan watermark: timestamp={sync_start_timestamp}, "
+                            f"file_count={current_file_count}"
+                        )
+
+            duration_ms = int((time.time() - start_time) * 1000)
+
+            # Log summary with skipped files if any
+            if report.skipped_files:
+                logger.warning(
+                    f"Sync completed with {len(report.skipped_files)} skipped files: "
+                    f"directory={directory}, total_changes={report.total}, "
+                    f"skipped={len(report.skipped_files)}, duration_ms={duration_ms}"
+                )
+                for skipped in report.skipped_files:
+                    logger.warning(
+                        f"Skipped file: path={skipped.path}, "
+                        f"failures={skipped.failure_count}, reason={skipped.reason}"
+                    )
+            else:
+                logger.info(
+                    f"Sync operation completed: directory={directory}, "
+                    f"total_changes={report.total}, duration_ms={duration_ms}"
+                )
+
+            return report
 
     async def scan(self, directory, force_full: bool = False):
         """Smart scan using watermark and file count for large project optimization.
@@ -407,171 +460,180 @@ class SyncService:
         if project is None:
             raise ValueError(f"Project not found: {self.entity_repository.project_id}")
 
-        # Step 1: Quick file count
-        logger.debug("Counting files in directory")
-        current_count = await self._quick_count_files(directory)
-        logger.debug(f"Found {current_count} files in directory")
+        with telemetry.scope("sync.project.select_scan_strategy", force_full=force_full):
+            # Step 1: Quick file count
+            logger.debug("Counting files in directory")
+            current_count = await self._quick_count_files(directory)
+            logger.debug(f"Found {current_count} files in directory")
 
-        # Step 2: Determine scan strategy based on watermark and file count
-        if force_full:
-            # User explicitly requested full scan → bypass watermark optimization
-            scan_type = "full_forced"
-            logger.info("Force full scan requested, bypassing watermark optimization")
-            file_paths_to_scan = await self._scan_directory_full(directory)
+            # Step 2: Determine scan strategy based on watermark and file count
+            if force_full:
+                # User explicitly requested full scan → bypass watermark optimization
+                scan_type = "full_forced"
+                logger.info("Force full scan requested, bypassing watermark optimization")
+                scan_coro = self._scan_directory_full(directory)
 
-        elif project.last_file_count is None:
-            # First sync ever → full scan
-            scan_type = "full_initial"
-            logger.info("First sync for this project, performing full scan")
-            file_paths_to_scan = await self._scan_directory_full(directory)
+            elif project.last_file_count is None:
+                # First sync ever → full scan
+                scan_type = "full_initial"
+                logger.info("First sync for this project, performing full scan")
+                scan_coro = self._scan_directory_full(directory)
 
-        elif current_count < project.last_file_count:
-            # Files deleted → need full scan to detect which ones
-            scan_type = "full_deletions"
-            logger.info(
-                f"File count decreased ({project.last_file_count} → {current_count}), "
-                f"running full scan to detect deletions"
-            )
-            file_paths_to_scan = await self._scan_directory_full(directory)
+            elif current_count < project.last_file_count:
+                # Files deleted → need full scan to detect which ones
+                scan_type = "full_deletions"
+                logger.info(
+                    f"File count decreased ({project.last_file_count} → {current_count}), "
+                    f"running full scan to detect deletions"
+                )
+                scan_coro = self._scan_directory_full(directory)
 
-        elif project.last_scan_timestamp is not None:
-            # Incremental scan: only files modified since last scan
-            scan_type = "incremental"
-            logger.info(
-                f"Running incremental scan for files modified since {project.last_scan_timestamp}"
-            )
-            file_paths_to_scan = await self._scan_directory_modified_since(
-                directory, project.last_scan_timestamp
-            )
-            logger.info(
-                f"Incremental scan found {len(file_paths_to_scan)} potentially changed files"
-            )
+            elif project.last_scan_timestamp is not None:
+                # Incremental scan: only files modified since last scan
+                scan_type = "incremental"
+                logger.debug(
+                    f"Running incremental scan for files modified since {project.last_scan_timestamp}"
+                )
+                scan_coro = self._scan_directory_modified_since(
+                    directory, project.last_scan_timestamp
+                )
 
-        else:
-            # Fallback to full scan (no watermark available)
-            scan_type = "full_fallback"
-            logger.warning("No scan watermark available, falling back to full scan")
-            file_paths_to_scan = await self._scan_directory_full(directory)
-
-        # Step 3: Process each file with mtime-based comparison
-        scanned_paths: Set[str] = set()
-        changed_checksums: Dict[str, str] = {}
-
-        logger.debug(f"Processing {len(file_paths_to_scan)} files with mtime-based comparison")
-
-        for rel_path in file_paths_to_scan:
-            scanned_paths.add(rel_path)
-
-            # Get file stats
-            abs_path = directory / rel_path
-            if not abs_path.exists():
-                # File was deleted between scan and now (race condition)
-                continue
-
-            stat_info = abs_path.stat()
-
-            # Indexed lookup - single file query (not full table scan)
-            db_entity = await self.entity_repository.get_by_file_path(rel_path)
-
-            if db_entity is None:
-                # New file - need checksum for move detection
-                checksum = await self.file_service.compute_checksum(rel_path)
-                report.new.add(rel_path)
-                changed_checksums[rel_path] = checksum
-                logger.trace(f"New file detected: {rel_path}")
-                continue
-
-            # File exists in DB - check if mtime/size changed
-            db_mtime = db_entity.mtime
-            db_size = db_entity.size
-            fs_mtime = stat_info.st_mtime
-            fs_size = stat_info.st_size
-
-            # Compare mtime and size (like rsync/rclone)
-            # Allow small epsilon for float comparison (0.01s = 10ms)
-            mtime_changed = db_mtime is None or abs(fs_mtime - db_mtime) > 0.01
-            size_changed = db_size is None or fs_size != db_size
-
-            if mtime_changed or size_changed:
-                # File modified - compute checksum
-                checksum = await self.file_service.compute_checksum(rel_path)
-                db_checksum = db_entity.checksum
-
-                # Only mark as modified if checksum actually differs
-                # (handles cases where mtime changed but content didn't, e.g., git operations)
-                if checksum != db_checksum:
-                    report.modified.add(rel_path)
-                    changed_checksums[rel_path] = checksum
-                    logger.trace(
-                        f"Modified file detected: {rel_path}, "
-                        f"mtime_changed={mtime_changed}, size_changed={size_changed}"
-                    )
             else:
-                # File unchanged - no checksum needed
-                logger.trace(f"File unchanged (mtime/size match): {rel_path}")
+                # Fallback to full scan (no watermark available)
+                scan_type = "full_fallback"
+                logger.warning("No scan watermark available, falling back to full scan")
+                scan_coro = self._scan_directory_full(directory)
 
-        # Step 4: Detect moves (for both full and incremental scans)
-        # Check if any "new" files are actually moves by matching checksums
-        for new_path in list(report.new):  # Use list() to allow modification during iteration
-            new_checksum = changed_checksums.get(new_path)
-            if not new_checksum:
-                continue
+        with telemetry.scope("sync.project.filesystem_scan", scan_type=scan_type):
+            file_paths_to_scan = await scan_coro
+            if scan_type == "incremental":
+                logger.debug(
+                    f"Incremental scan found {len(file_paths_to_scan)} potentially changed files"
+                )
 
-            # Look for existing entity with same checksum but different path
-            # This could be a move or a copy
-            existing_entities = await self.entity_repository.find_by_checksum(new_checksum)
+            # Step 3: Process each file with mtime-based comparison
+            scanned_paths: Set[str] = set()
+            changed_checksums: Dict[str, str] = {}
 
-            for candidate in existing_entities:
-                if candidate.file_path == new_path:
-                    # Same path, skip (shouldn't happen for "new" files but be safe)
+            logger.debug(f"Processing {len(file_paths_to_scan)} files with mtime-based comparison")
+
+            for rel_path in file_paths_to_scan:
+                scanned_paths.add(rel_path)
+
+                # Get file stats
+                abs_path = directory / rel_path
+                if not abs_path.exists():
+                    # File was deleted between scan and now (race condition)
                     continue
 
-                # Check if the old path still exists on disk
-                old_path_abs = directory / candidate.file_path
-                if old_path_abs.exists():
-                    # Original still exists → this is a copy, not a move
-                    logger.trace(
-                        f"File copy detected (not move): {candidate.file_path} copied to {new_path}"
-                    )
+                stat_info = abs_path.stat()
+
+                # Indexed lookup - single file query (not full table scan)
+                db_entity = await self.entity_repository.get_by_file_path(rel_path)
+
+                if db_entity is None:
+                    # New file - need checksum for move detection
+                    checksum = await self.file_service.compute_checksum(rel_path)
+                    report.new.add(rel_path)
+                    changed_checksums[rel_path] = checksum
+                    logger.trace(f"New file detected: {rel_path}")
                     continue
 
-                # Original doesn't exist → this is a move!
-                report.moves[candidate.file_path] = new_path
-                report.new.remove(new_path)
-                logger.trace(f"Move detected: {candidate.file_path} -> {new_path}")
-                break  # Only match first candidate
+                # File exists in DB - check if mtime/size changed
+                db_mtime = db_entity.mtime
+                db_size = db_entity.size
+                fs_mtime = stat_info.st_mtime
+                fs_size = stat_info.st_size
 
-        # Step 5: Detect deletions (only for full scans)
-        # Incremental scans can't reliably detect deletions since they only see modified files
-        if scan_type in ("full_initial", "full_deletions", "full_fallback", "full_forced"):
-            # Use optimized query for just file paths (not full entities)
-            db_file_paths = await self.entity_repository.get_all_file_paths()
-            logger.debug(f"Found {len(db_file_paths)} db paths for deletion detection")
+                # Compare mtime and size (like rsync/rclone)
+                # Allow small epsilon for float comparison (0.01s = 10ms)
+                mtime_changed = db_mtime is None or abs(fs_mtime - db_mtime) > 0.01
+                size_changed = db_size is None or fs_size != db_size
 
-            for db_path in db_file_paths:
-                if db_path not in scanned_paths:
-                    # File in DB but not on filesystem
-                    # Check if it was already detected as a move
-                    if db_path in report.moves:
-                        # Already handled as a move, skip
+                if mtime_changed or size_changed:
+                    # File modified - compute checksum
+                    checksum = await self.file_service.compute_checksum(rel_path)
+                    db_checksum = db_entity.checksum
+
+                    # Only mark as modified if checksum actually differs
+                    # (handles cases where mtime changed but content didn't, e.g., git operations)
+                    if checksum != db_checksum:
+                        report.modified.add(rel_path)
+                        changed_checksums[rel_path] = checksum
+                        logger.trace(
+                            f"Modified file detected: {rel_path}, "
+                            f"mtime_changed={mtime_changed}, size_changed={size_changed}"
+                        )
+                else:
+                    # File unchanged - no checksum needed
+                    logger.trace(f"File unchanged (mtime/size match): {rel_path}")
+
+            # Step 4: Detect moves (for both full and incremental scans)
+            # Check if any "new" files are actually moves by matching checksums
+            with telemetry.scope("sync.project.detect_moves", new_count=len(report.new)):
+                for new_path in list(
+                    report.new
+                ):  # Use list() to allow modification during iteration
+                    new_checksum = changed_checksums.get(new_path)
+                    if not new_checksum:
                         continue
 
-                    # File was deleted
-                    report.deleted.add(db_path)
-                    logger.trace(f"Deleted file detected: {db_path}")
+                    # Look for existing entity with same checksum but different path
+                    # This could be a move or a copy
+                    existing_entities = await self.entity_repository.find_by_checksum(new_checksum)
 
-        # Store checksums for files that need syncing
-        report.checksums = changed_checksums
+                    for candidate in existing_entities:
+                        if candidate.file_path == new_path:
+                            # Same path, skip (shouldn't happen for "new" files but be safe)
+                            continue
 
-        scan_duration_ms = int((time.time() - scan_start_time) * 1000)
+                        # Check if the old path still exists on disk
+                        old_path_abs = directory / candidate.file_path
+                        if old_path_abs.exists():
+                            # Original still exists → this is a copy, not a move
+                            logger.trace(
+                                f"File copy detected (not move): {candidate.file_path} copied to {new_path}"
+                            )
+                            continue
 
-        logger.info(
-            f"Completed {scan_type} scan for directory {directory} in {scan_duration_ms}ms, "
-            f"found {report.total} changes (new={len(report.new)}, "
-            f"modified={len(report.modified)}, deleted={len(report.deleted)}, "
-            f"moves={len(report.moves)})"
-        )
-        return report
+                        # Original doesn't exist → this is a move!
+                        report.moves[candidate.file_path] = new_path
+                        report.new.remove(new_path)
+                        logger.trace(f"Move detected: {candidate.file_path} -> {new_path}")
+                        break  # Only match first candidate
+
+            # Step 5: Detect deletions (only for full scans)
+            # Incremental scans can't reliably detect deletions since they only see modified files
+            if scan_type in ("full_initial", "full_deletions", "full_fallback", "full_forced"):
+                with telemetry.scope("sync.project.detect_deletions", scan_type=scan_type):
+                    # Use optimized query for just file paths (not full entities)
+                    db_file_paths = await self.entity_repository.get_all_file_paths()
+                    logger.debug(f"Found {len(db_file_paths)} db paths for deletion detection")
+
+                    for db_path in db_file_paths:
+                        if db_path not in scanned_paths:
+                            # File in DB but not on filesystem
+                            # Check if it was already detected as a move
+                            if db_path in report.moves:
+                                # Already handled as a move, skip
+                                continue
+
+                            # File was deleted
+                            report.deleted.add(db_path)
+                            logger.trace(f"Deleted file detected: {db_path}")
+
+            # Store checksums for files that need syncing
+            report.checksums = changed_checksums
+
+            scan_duration_ms = int((time.time() - scan_start_time) * 1000)
+
+            logger.info(
+                f"Completed {scan_type} scan for directory {directory} in {scan_duration_ms}ms, "
+                f"found {report.total} changes (new={len(report.new)}, "
+                f"modified={len(report.modified)}, deleted={len(report.deleted)}, "
+                f"moves={len(report.moves)})"
+            )
+            return report
 
     async def sync_file(
         self, path: str, new: bool = True
@@ -590,12 +652,14 @@ class SyncService:
             logger.warning(f"Skipping file due to repeated failures: {path}")
             return None, None
 
-        try:
-            logger.debug(
-                f"Syncing file path={path} is_new={new} is_markdown={self.file_service.is_markdown(path)}"
-            )
+        start_time = time.time()
+        is_markdown = self.file_service.is_markdown(path)
+        file_kind = "markdown" if is_markdown else "regular"
 
-            if self.file_service.is_markdown(path):
+        try:
+            logger.debug(f"Syncing file path={path} is_new={new} is_markdown={is_markdown}")
+
+            if is_markdown:
                 entity, checksum = await self.sync_markdown_file(path, new)
             else:
                 entity, checksum = await self.sync_regular_file(path, new)
@@ -620,33 +684,63 @@ class SyncService:
                 logger.debug(
                     f"File sync completed, path={path}, entity_id={entity.id}, checksum={checksum[:8]}"
                 )
+            duration_ms = int((time.time() - start_time) * 1000)
+            if duration_ms >= SLOW_FILE_SYNC_WARNING_MS:
+                logger.warning(
+                    f"Slow file sync detected: path={path}, file_kind={file_kind}, duration_ms={duration_ms}"
+                )
             return entity, checksum
 
         except FileNotFoundError:
             # File exists in database but not on filesystem
             # This indicates a database/filesystem inconsistency - treat as deletion
-            logger.warning(
-                f"File not found during sync, treating as deletion: path={path}. "
-                "This may indicate a race condition or manual file deletion."
-            )
-            await self.handle_delete(path)
+            with telemetry.scope(
+                "sync.file.failure",
+                failure_type="file_not_found",
+                path=path,
+                file_kind=file_kind,
+                is_new=new,
+                is_fatal=False,
+            ):
+                logger.warning(
+                    f"File not found during sync, treating as deletion: path={path}. "
+                    "This may indicate a race condition or manual file deletion."
+                )
+                await self.handle_delete(path)
             return None, None
 
         except Exception as e:
+            failure_type = type(e).__name__
             # Check if this is a fatal error (or caused by one)
             # Fatal errors like project deletion should terminate sync immediately
             if isinstance(e, SyncFatalError) or isinstance(
                 e.__cause__, SyncFatalError
             ):  # pragma: no cover
-                logger.error(f"Fatal sync error encountered, terminating sync: path={path}")
+                with telemetry.scope(
+                    "sync.file.failure",
+                    failure_type=failure_type,
+                    path=path,
+                    file_kind=file_kind,
+                    is_new=new,
+                    is_fatal=True,
+                ):
+                    logger.error(f"Fatal sync error encountered, terminating sync: path={path}")
                 raise
 
             # Otherwise treat as recoverable file-level error
             error_msg = str(e)
-            logger.error(f"Failed to sync file: path={path}, error={error_msg}")
+            with telemetry.scope(
+                "sync.file.failure",
+                failure_type=failure_type,
+                path=path,
+                file_kind=file_kind,
+                is_new=new,
+                is_fatal=False,
+            ):
+                logger.error(f"Failed to sync file: path={path}, error={error_msg}")
 
-            # Record failure for circuit breaker
-            await self._record_failure(path, error_msg)
+                # Record failure for circuit breaker
+                await self._record_failure(path, error_msg)
 
             return None, None
 
@@ -705,7 +799,7 @@ class SyncService:
 
             # If permalink changed, update the file
             if permalink != entity_markdown.frontmatter.permalink:
-                logger.info(
+                logger.debug(
                     f"Updating permalink for path: {path}, old_permalink: {entity_markdown.frontmatter.permalink}, new_permalink: {permalink}"
                 )
 
@@ -1040,24 +1134,36 @@ class SyncService:
                     # update search index only on successful resolution
                     await self.search_service.index_entity(resolved_entity)
                 except IntegrityError:
-                    # IntegrityError means a relation with this (from_id, to_id, relation_type)
-                    # already exists. The UPDATE was rolled back, so our unresolved relation
-                    # (to_id=NULL) still exists in the database. We delete it because:
-                    # 1. It's redundant - a resolved relation already captures this relationship
-                    # 2. If we don't delete it, future syncs will try to resolve it again
-                    #    and get the same IntegrityError
-                    logger.debug(
-                        "Deleting duplicate unresolved relation "
-                        f"relation_id={relation.id} "
-                        f"from_id={relation.from_id} "
-                        f"to_name={relation.to_name} "
-                        f"resolved_to_id={resolved_entity.id}"
-                    )
-                    try:
-                        await self.relation_repository.delete(relation.id)
-                    except Exception as e:
-                        # Log but don't fail - the relation may have been deleted already
-                        logger.debug(f"Could not delete duplicate relation {relation.id}: {e}")
+                    with telemetry.scope(
+                        "sync.relation.resolve_conflict",
+                        relation_id=relation.id,
+                        relation_type=relation.relation_type,
+                    ):
+                        # IntegrityError means a relation with this (from_id, to_id, relation_type)
+                        # already exists. The UPDATE was rolled back, so our unresolved relation
+                        # (to_id=NULL) still exists in the database. We delete it because:
+                        # 1. It's redundant - a resolved version already captures this relationship
+                        # 2. If we don't delete it, future syncs will try to resolve it again
+                        #    and get the same IntegrityError
+                        logger.debug(
+                            "Deleting duplicate unresolved relation "
+                            f"relation_id={relation.id} "
+                            f"from_id={relation.from_id} "
+                            f"to_name={relation.to_name} "
+                            f"resolved_to_id={resolved_entity.id}"
+                        )
+                        try:
+                            await self.relation_repository.delete(relation.id)
+                        except Exception as e:
+                            with telemetry.scope(
+                                "sync.relation.cleanup_failure",
+                                relation_id=relation.id,
+                                relation_type=relation.relation_type,
+                            ):
+                                # Log but don't fail - the relation may have been deleted already
+                                logger.debug(
+                                    f"Could not delete duplicate relation {relation.id}: {e}"
+                                )
 
     async def _quick_count_files(self, directory: Path) -> int:
         """Fast file count using find command.

src/basic_memory/telemetry.py

@@ -0,0 +1,189 @@
+"""Optional Logfire telemetry helpers for Basic Memory.
+
+Telemetry is disabled by default. When enabled, this module configures Logfire,
+exposes a `loguru` handler for trace-aware logging, and provides lightweight
+helpers for manual spans and logger context binding.
+"""
+
+from __future__ import annotations
+
+from contextlib import contextmanager
+from dataclasses import dataclass, field
+from typing import Any, Iterator
+
+from loguru import logger
+
+REPOSITORY_URL = "https://github.com/basicmachines-co/basic-memory"
+ROOT_PATH = "src/basic_memory"
+
+
+def _load_logfire() -> Any | None:
+    """Load the optional logfire dependency lazily."""
+    try:
+        import logfire
+    except ImportError:
+        return None
+    return logfire
+
+
+@dataclass
+class TelemetryState:
+    """Process-local Logfire configuration state."""
+
+    enabled: bool = False
+    configured: bool = False
+    service_name: str | None = None
+    environment: str | None = None
+    send_to_logfire: bool = False
+    warnings: list[str] = field(default_factory=list)
+
+
+_STATE = TelemetryState()
+_LOGFIRE_HANDLER: dict[str, Any] | None = None
+
+
+def reset_telemetry_state() -> None:
+    """Reset process-local telemetry state.
+
+    Primarily used by tests.
+    """
+    global _LOGFIRE_HANDLER
+    _STATE.enabled = False
+    _STATE.configured = False
+    _STATE.service_name = None
+    _STATE.environment = None
+    _STATE.send_to_logfire = False
+    _STATE.warnings.clear()
+    _LOGFIRE_HANDLER = None
+
+
+def _filter_attributes(attrs: dict[str, Any]) -> dict[str, Any]:
+    """Drop null attributes so span and log payloads stay compact."""
+    return {key: value for key, value in attrs.items() if value is not None}
+
+
+def configure_telemetry(
+    service_name: str,
+    *,
+    environment: str,
+    service_version: str | None = None,
+    enable_logfire: bool = False,
+    send_to_logfire: bool = False,
+    log_level: str = "INFO",
+) -> bool:
+    """Configure optional Logfire instrumentation for the current process."""
+    global _LOGFIRE_HANDLER
+
+    reset_telemetry_state()
+    _STATE.service_name = service_name
+    _STATE.environment = environment
+    _STATE.send_to_logfire = send_to_logfire
+    _STATE.enabled = enable_logfire
+
+    if not enable_logfire:
+        return False
+
+    logfire = _load_logfire()
+    if logfire is None:
+        _STATE.enabled = False
+        _STATE.warnings.append(
+            "Logfire telemetry was enabled but the 'logfire' package is not installed. "
+            "Telemetry remains disabled."
+        )
+        return False
+
+    configure_kwargs = {
+        "service_name": service_name,
+        "environment": environment,
+        "code_source": logfire.CodeSource(
+            repository=REPOSITORY_URL,
+            revision=service_version or "",
+            root_path=ROOT_PATH,
+        ),
+        "min_level": log_level.lower(),
+        "send_to_logfire": send_to_logfire,
+    }
+
+    try:
+        logfire.configure(**configure_kwargs)
+    except TypeError:
+        configure_kwargs.pop("send_to_logfire", None)
+        logfire.configure(**configure_kwargs)
+    except Exception as exc:  # pragma: no cover
+        _STATE.enabled = False  # pragma: no cover
+        _STATE.warnings.append(f"Failed to configure Logfire telemetry: {exc}")  # pragma: no cover
+        return False  # pragma: no cover
+
+    _LOGFIRE_HANDLER = logfire.loguru_handler()
+    _STATE.configured = True
+    return True
+
+
+def telemetry_enabled() -> bool:
+    """Return True when telemetry is both enabled and configured."""
+    return _STATE.enabled and _STATE.configured
+
+
+def get_logfire_handler() -> dict[str, Any] | None:
+    """Return the active Logfire `loguru` handler, if any."""
+    return _LOGFIRE_HANDLER
+
+
+def pop_telemetry_warnings() -> list[str]:
+    """Return and clear pending telemetry warnings."""
+    warnings = list(_STATE.warnings)
+    _STATE.warnings.clear()
+    return warnings
+
+
+@contextmanager
+def contextualize(**attrs: Any) -> Iterator[None]:
+    """Apply filtered telemetry attributes to Loguru calls in this scope."""
+    with logger.contextualize(**_filter_attributes(attrs)):
+        yield
+
+
+@contextmanager
+def scope(name: str, **attrs: Any) -> Iterator[None]:
+    """Create a span and bind the same stable attributes into Loguru context."""
+    with contextualize(**attrs):
+        with span(name, **attrs):
+            yield
+
+
+# Alias: `operation` signals a root-level boundary (entrypoint, tool invocation),
+# while `scope` signals a nested phase. The distinction is convention only.
+operation = scope
+
+
+@contextmanager
+def span(name: str, **attrs: Any) -> Iterator[None]:
+    """Create a manual Logfire span when telemetry is enabled."""
+    with started_span(name, **attrs):
+        yield
+
+
+@contextmanager
+def started_span(name: str, **attrs: Any) -> Iterator[Any | None]:
+    """Create a manual Logfire span and expose the active span handle when available."""
+    logfire = _load_logfire()
+    if logfire is None or not _STATE.configured:  # pragma: no cover
+        yield  # pragma: no cover
+        return  # pragma: no cover
+
+    with logfire.span(name, **_filter_attributes(attrs)) as active_span:
+        yield active_span
+
+
+__all__ = [
+    "contextualize",
+    "configure_telemetry",
+    "get_logfire_handler",
+    "operation",
+    "pop_telemetry_warnings",
+    "reset_telemetry_state",
+    "scope",
+    "span",
+    "started_span",
+    "telemetry_enabled",
+]