chore: update version to 0.19.0 for v0.19.0 release

Comprehensive changelog for 114 commits since v0.18.5 covering semantic
vector search, schema system, per-project cloud routing, FastMCP 3.0
upgrade, CLI overhaul, and numerous bug fixes.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Signed-off-by: phernandez <paul@basicmachines.co>

CHANGELOG.md

@@ -2,13 +2,139 @@
 
 ## Unreleased
 
+## 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)
 

server.json

@@ -6,12 +6,12 @@
     "url": "https://github.com/basicmachines-co/basic-memory.git",
     "source": "github"
   },
-  "version": "0.18.5",
+  "version": "0.19.0",
   "packages": [
     {
       "registryType": "pypi",
       "identifier": "basic-memory",
-      "version": "0.18.5",
+      "version": "0.19.0",
       "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__ = "0.19.0"
 
 # API version for FastAPI - independent of package version
 __api_version__ = "v0"

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"
 )
 
 

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(
@@ -480,26 +477,9 @@ async def run_migrations(
     Note: Alembic tracks which migrations have been applied via the alembic_version table,
     so it's safe to call this multiple times - it will only run pending migrations.
     """
-    logger.debug("Running database 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()
@@ -519,7 +499,7 @@ async def run_migrations(
         config.set_main_option("sqlalchemy.url", db_url)
 
         command.upgrade(config, "head")
-        logger.debug("Migrations completed successfully")
+        logger.info("Migrations completed successfully")
 
         # Get session maker - ensure we don't trigger recursive migration calls
         if _session_maker is None:
@@ -541,12 +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/mcp/server.py

@@ -2,18 +2,71 @@
 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
 
 
+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
 async def lifespan(app: FastMCP):
     """Lifecycle manager for the MCP server.
@@ -70,6 +123,16 @@ async def lifespan(app: FastMCP):
     # Initialize app (runs migrations, reconciles projects)
     await initialize_app(container.config)
 
+    # 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()
@@ -79,6 +142,15 @@ async def lifespan(app: FastMCP):
     finally:
         # Shutdown - coordinator handles clean task cancellation
         logger.debug("Shutting down Basic Memory MCP server")
+
+        # 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)

src/basic_memory/mcp/tools/schema.py

@@ -160,7 +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"
@@ -397,7 +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"

src/basic_memory/mcp/tools/search.py

@@ -2,7 +2,7 @@
 
 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
@@ -165,7 +165,7 @@ 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"])`
 
@@ -305,8 +305,17 @@ async def search_notes(
     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,
+        "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,
@@ -350,6 +359,7 @@ async def search_notes(
     ### 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)
 
@@ -436,7 +446,7 @@ 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"],
@@ -477,7 +487,8 @@ 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.

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/sync/sync_service.py

@@ -293,12 +293,16 @@ class SyncService:
         for path in report.deleted:
             await self.handle_delete(path)
 
-        # then new and modified
+        # 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
-            if entity is None and await self._should_skip_file(path):
+            elif await self._should_skip_file(path):
                 failure_info = self._file_failures[path]
                 report.skipped_files.append(
                     SkippedFile(
@@ -312,8 +316,10 @@ class SyncService:
         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
-            if entity is None and await self._should_skip_file(path):
+            elif await self._should_skip_file(path):
                 failure_info = self._file_failures[path]
                 report.skipped_files.append(
                     SkippedFile(
@@ -331,6 +337,26 @@ class SyncService:
         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:
+                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

tests/mcp/test_project_context.py

@@ -31,6 +31,7 @@ async def test_returns_none_when_no_default_and_no_project(config_manager, monke
     config_manager.save_config(cfg)
 
     monkeypatch.delenv("BASIC_MEMORY_MCP_PROJECT", raising=False)
+
     # Prevent API fallback from returning a project via stale dependency overrides
     async def _no_api_fallback():
         return None
@@ -117,6 +118,7 @@ async def test_returns_none_when_no_default(config_manager, monkeypatch):
     config_manager.save_config(cfg)
 
     monkeypatch.delenv("BASIC_MEMORY_MCP_PROJECT", raising=False)
+
     # Prevent API fallback from returning a project via stale dependency overrides
     async def _no_api_fallback():
         return None

tests/mcp/test_tool_search.py

@@ -1146,6 +1146,54 @@ async def test_search_notes_explicit_entity_types_overrides_default(monkeypatch)
     assert captured_payload["entity_types"] == ["observation"]
 
 
+# --- Tests for note_types case-insensitivity ------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_search_notes_note_types_lowercased(monkeypatch):
+    """note_types values are lowercased so 'Chapter' matches stored 'chapter'."""
+    import importlib
+
+    search_mod = importlib.import_module("basic_memory.mcp.tools.search")
+    clients_mod = importlib.import_module("basic_memory.mcp.clients")
+
+    class StubProject:
+        name = "test-project"
+        external_id = "test-external-id"
+
+    @asynccontextmanager
+    async def fake_get_project_client(*args, **kwargs):
+        yield (object(), StubProject())
+
+    async def fake_resolve_project_and_path(
+        client, identifier, project=None, context=None, headers=None
+    ):
+        return StubProject(), identifier, False
+
+    captured_payload: dict = {}
+
+    class MockSearchClient:
+        def __init__(self, *args, **kwargs):
+            pass
+
+        async def search(self, payload, page, page_size):
+            captured_payload.update(payload)
+            return SearchResponse(results=[], current_page=page, page_size=page_size)
+
+    monkeypatch.setattr(search_mod, "get_project_client", fake_get_project_client)
+    monkeypatch.setattr(search_mod, "resolve_project_and_path", fake_resolve_project_and_path)
+    monkeypatch.setattr(clients_mod, "SearchClient", MockSearchClient)
+
+    await search_mod.search_notes(
+        project="test-project",
+        query="test",
+        note_types=["Chapter", "Person"],
+    )
+
+    # note_types should be lowercased
+    assert captured_payload["note_types"] == ["chapter", "person"]
+
+
 # --- Tests for tag: prefix parsing (issue #30) ---------------------------------
 
 

tests/services/test_initialization.py

@@ -200,10 +200,10 @@ async def test_initialize_app_no_precedence_warning_when_not_conflicting(
 
 
 @pytest.mark.asyncio
-async def test_run_migrations_triggers_embedding_backfill_on_new_revision(
+async def test_run_migrations_triggers_embedding_backfill_when_entities_exist_but_no_embeddings(
     monkeypatch, app_config: BasicMemoryConfig
 ):
-    """When the trigger revision is newly applied, run automatic embedding backfill once."""
+    """run_migrations checks for missing embeddings (actual backfill runs in background from MCP)."""
 
     class StubSearchRepository:
         def __init__(self, *args, **kwargs):
@@ -224,29 +224,24 @@ async def test_run_migrations_triggers_embedding_backfill_on_new_revision(
         monkeypatch.setattr("basic_memory.db.SQLiteSearchRepository", StubSearchRepository)
         monkeypatch.setattr("basic_memory.db.PostgresSearchRepository", StubSearchRepository)
 
-        load_revisions_mock = AsyncMock(
-            side_effect=[
-                set(),
-                {db.SEMANTIC_EMBEDDING_BACKFILL_REVISION},
-            ]
+        needs_backfill_mock = AsyncMock(return_value=True)
+        monkeypatch.setattr(
+            "basic_memory.db._needs_semantic_embedding_backfill", needs_backfill_mock
         )
-        backfill_mock = AsyncMock()
-        monkeypatch.setattr("basic_memory.db._load_applied_alembic_revisions", load_revisions_mock)
-        monkeypatch.setattr("basic_memory.db._run_semantic_embedding_backfill", backfill_mock)
 
         await db.run_migrations(app_config)
 
-        assert load_revisions_mock.await_count == 2
-        backfill_mock.assert_awaited_once_with(app_config, session_marker)
+        # Verifies the check runs — backfill itself is launched by MCP lifespan
+        needs_backfill_mock.assert_awaited_once_with(app_config, session_marker)
     finally:
         db._session_maker = original_session_maker  # pyright: ignore [reportPrivateUsage]
 
 
 @pytest.mark.asyncio
-async def test_run_migrations_skips_embedding_backfill_when_revision_already_applied(
+async def test_run_migrations_skips_embedding_backfill_when_embeddings_already_exist(
     monkeypatch, app_config: BasicMemoryConfig
 ):
-    """If the trigger revision was already present before upgrade, skip backfill."""
+    """When embeddings already exist, no backfill is needed."""
 
     class StubSearchRepository:
         def __init__(self, *args, **kwargs):
@@ -267,20 +262,14 @@ async def test_run_migrations_skips_embedding_backfill_when_revision_already_app
         monkeypatch.setattr("basic_memory.db.SQLiteSearchRepository", StubSearchRepository)
         monkeypatch.setattr("basic_memory.db.PostgresSearchRepository", StubSearchRepository)
 
-        load_revisions_mock = AsyncMock(
-            side_effect=[
-                {db.SEMANTIC_EMBEDDING_BACKFILL_REVISION},
-                {db.SEMANTIC_EMBEDDING_BACKFILL_REVISION},
-            ]
+        needs_backfill_mock = AsyncMock(return_value=False)
+        monkeypatch.setattr(
+            "basic_memory.db._needs_semantic_embedding_backfill", needs_backfill_mock
         )
-        backfill_mock = AsyncMock()
-        monkeypatch.setattr("basic_memory.db._load_applied_alembic_revisions", load_revisions_mock)
-        monkeypatch.setattr("basic_memory.db._run_semantic_embedding_backfill", backfill_mock)
 
         await db.run_migrations(app_config)
 
-        assert load_revisions_mock.await_count == 2
-        assert backfill_mock.await_count == 0
+        needs_backfill_mock.assert_awaited_once_with(app_config, session_marker)
     finally:
         db._session_maker = original_session_maker  # pyright: ignore [reportPrivateUsage]
 
@@ -378,3 +367,58 @@ async def test_semantic_embedding_backfill_skips_when_semantic_disabled(
     app_config.semantic_search_enabled = False
     await db._run_semantic_embedding_backfill(app_config, session_maker)  # pyright: ignore [reportPrivateUsage]
     assert called is False
+
+
+@pytest.mark.asyncio
+async def test_needs_semantic_embedding_backfill_true_when_entities_exist_no_embeddings(
+    app_config: BasicMemoryConfig,
+    session_maker,
+    test_project,
+):
+    """Should return True when entities exist but vector chunks table is empty."""
+    from basic_memory.repository.entity_repository import EntityRepository
+
+    entity_repository = EntityRepository(session_maker, project_id=test_project.id)
+    await entity_repository.create(
+        {
+            "title": "Test Entity",
+            "note_type": "note",
+            "entity_metadata": {},
+            "content_type": "text/markdown",
+            "file_path": "test/backfill-check.md",
+            "permalink": "test/backfill-check",
+            "project_id": test_project.id,
+            "created_at": datetime.now(),
+            "updated_at": datetime.now(),
+        }
+    )
+
+    # Clear any embeddings left by other tests in the shared DB
+    async with db.scoped_session(session_maker) as session:
+        await session.execute(db.text("DELETE FROM search_vector_chunks"))
+
+    app_config.semantic_search_enabled = True
+    result = await db._needs_semantic_embedding_backfill(app_config, session_maker)  # pyright: ignore [reportPrivateUsage]
+    assert result is True
+
+
+@pytest.mark.asyncio
+async def test_needs_semantic_embedding_backfill_false_when_no_entities(
+    app_config: BasicMemoryConfig,
+    session_maker,
+):
+    """Should return False when no entities exist (nothing to backfill)."""
+    app_config.semantic_search_enabled = True
+    result = await db._needs_semantic_embedding_backfill(app_config, session_maker)  # pyright: ignore [reportPrivateUsage]
+    assert result is False
+
+
+@pytest.mark.asyncio
+async def test_needs_semantic_embedding_backfill_false_when_semantic_disabled(
+    app_config: BasicMemoryConfig,
+    session_maker,
+):
+    """Should return False when semantic search is disabled."""
+    app_config.semantic_search_enabled = False
+    result = await db._needs_semantic_embedding_backfill(app_config, session_maker)  # pyright: ignore [reportPrivateUsage]
+    assert result is False