add user guide docs

Signed-off-by: phernandez <paul@basicmachines.co>
This commit is contained in:
phernandez
2025-03-07 14:11:06 -06:00
parent 9bb8a020c3
commit 2d5176e800
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@@ -20,6 +20,14 @@ 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.
LLMs can build context from local knowledge bases.
![Example Gif](docs/attachments/Obsidian-CoffeeKnowledgeBase-examples-overlays.gif)
Basic Memory provides persistent contextual awareness across sessions through a structured knowledge graph.
The system enables LLMs to access and reference prior conversations, track semantic relationships between concepts, and
incorporate human edits made directly to knowledge files.
## Quick Start
```bash
@@ -39,18 +47,43 @@ uv install basic-memory
}
}
}
# Start real-time sync
basic-memory sync --watch
# Now in Claude Desktop, you can:
# - Write notes with "Create a note about coffee brewing methods"
# - Read notes with "What do I know about pour over coffee?"
# - Search with "Find information about Ethiopian beans"
# View files shared context via files in ~/basic-memory
```
You can view shared context via files in `~/basic-memory` (default directory location).
You can also install the cli tools to sync files or manage projects.
```bash
uv tool install basic-memory
# create a new project in a different directory
basic-memory project add coffee ./examples/coffee
# you can set the project to the default
basic-memory project default coffee
```
View available projects
```bash
basic-memory project list
Basic Memory Projects
┏━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━┓
┃ Name ┃ Path ┃ Default ┃ Active ┃
┡━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━┩
│ main │ ~/basic-memory │ ✓ │ ✓ │
│ coffee │ ~/dev/basicmachines/basic-memory/examples/coffee │ │ │
└────────┴──────────────────────────────────────────────────┴─────────┴────────┘
```
Basic Memory will write notes in Markdown format. Open you project directory in your text editor to view project files
while you have conversations with an LLM.
## Why Basic Memory?
Most LLM interactions are ephemeral - you ask a question, get an answer, and everything is forgotten. Each conversation
@@ -61,7 +94,8 @@ starts fresh, without the context or knowledge from previous ones. Current worka
- Vector databases require complex setups and often live in the cloud
- Knowledge graphs typically need specialized tools to maintain
Basic Memory solves these problems with a simple approach: structured Markdown files that both humans and LLMs can read
Basic Memory addresses these problems with a simple approach: structured Markdown files that both humans and LLMs can
read
and write to. The key advantages:
- **Local-first:** All knowledge stays in files you control
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{}
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{}
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{
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"included": [],
"excluded": []
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"icon": "links-coming-in",
"title": "Backlinks"
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{
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"type": "leaf",
"state": {
"type": "outgoing-link",
"state": {
"linksCollapsed": false,
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"icon": "links-going-out",
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---
title: AI Assistant Guide
type: note
permalink: docs/ai-assistant-guide
---
# AI Assistant Guide for Basic Memory
This guide helps you, the AI assistant, use Basic Memory tools effectively when working with users. It covers reading, writing, and navigating knowledge through the Model Context Protocol (MCP).
## Overview
Basic Memory allows you and users to record context in local Markdown files, building a rich knowledge base through natural conversations. The system automatically creates a semantic knowledge graph from simple text patterns.
- **Local-First**: All data is stored in plain text files on the user's computer
- **Real-Time**: Users see content updates immediately
- **Bi-Directional**: Both you and users can read and edit notes
- **Semantic**: Simple patterns create a structured knowledge graph
- **Persistent**: Knowledge persists across sessions and conversations
## The Importance of the Knowledge Graph
Basic Memory's value comes from connections between notes, not just the notes themselves. When writing notes, your primary goal should be creating a rich, interconnected knowledge graph.
When creating content, focus on:
1. **Increasing Semantic Density**: Add multiple observations and relations to each note
2. **Using Accurate References**: Aim to reference existing entities by their exact titles
3. **Creating Forward References**: Feel free to reference entities that don't exist yet - Basic Memory will resolve these when they're created later
4. **Creating Bidirectional Links**: When appropriate, connect entities from both directions
5. **Using Meaningful Categories**: Add semantic context with appropriate observation categories
6. **Choosing Precise Relations**: Use specific relation types that convey meaning
Remember that a knowledge graph with 10 heavily connected notes is more valuable than 20 isolated notes. Your job is to help build these connections.
## Core Tools Reference
```python
# Writing knowledge - THE MOST IMPORTANT TOOL!
response = await write_note(
title="Search Design", # Required: Note title
content="# Search Design\n...", # Required: Note content
folder="specs", # Optional: Folder to save in
tags=["search", "design"], # Optional: Tags for categorization
verbose=True # Optional: Get parsing details
)
# Reading knowledge
content = await read_note("Search Design") # By title
content = await read_note("specs/search-design") # By path
content = await read_note("memory://specs/search") # By memory URL
# Searching for knowledge
results = await search(
query="authentication system", # Text to search for
page=1, # Optional: Pagination
page_size=10 # Optional: Results per page
)
# Building context from the knowledge graph
context = await build_context(
url="memory://specs/search", # Starting point
depth=2, # Optional: How many hops to follow
timeframe="1 month" # Optional: Recent timeframe
)
# Checking recent changes
activity = await recent_activity(
type="all", # Optional: Entity types to include
depth=1, # Optional: Related items to include
timeframe="1 week" # Optional: Time window
)
# Creating a knowledge visualization
canvas_result = await canvas(
nodes=[{"id": "note1", "label": "Search Design"}], # Nodes to display
edges=[{"from": "note1", "to": "note2"}], # Connections
title="Project Overview", # Canvas title
folder="diagrams" # Storage location
)
```
## memory:// URLs Explained
Basic Memory uses a special URL format to reference entities in the knowledge graph:
- `memory://title` - Reference by title
- `memory://folder/title` - Reference by folder and title
- `memory://permalink` - Reference by permalink
- `memory://path/relation_type/*` - Follow all relations of a specific type
- `memory://path/*/target` - Find all entities with relations to target
## Semantic Markdown Format
Knowledge is encoded in standard markdown using simple patterns:
**Observations** - Facts about an entity:
```markdown
- [category] This is an observation #tag1 #tag2 (optional context)
```
**Relations** - Links between entities:
```markdown
- relation_type [[Target Entity]] (optional context)
```
**Common Categories & Relation Types:**
- Categories: `[idea]`, `[decision]`, `[question]`, `[fact]`, `[requirement]`, `[technique]`, `[recipe]`, `[preference]`
- Relations: `relates_to`, `implements`, `requires`, `extends`, `part_of`, `pairs_with`, `inspired_by`, `originated_from`
## When to Record Context
**Always consider recording context when**:
1. Users make decisions or reach conclusions
2. Important information emerges during conversation
3. Multiple related topics are discussed
4. The conversation contains information that might be useful later
5. Plans, tasks, or action items are mentioned
**Protocol for recording context**:
1. Identify valuable information in the conversation
2. Ask the user: "Would you like me to record our discussion about [topic] in Basic Memory?"
3. If they agree, use `write_note` to capture the information
4. If they decline, continue without recording
5. Let the user know when information has been recorded: "I've saved our discussion about [topic] to Basic Memory."
## Understanding User Interactions
Users will interact with Basic Memory in patterns like:
1. **Creating knowledge**:
```
Human: "Let's write up what we discussed about search."
You: I'll create a note capturing our discussion about the search functionality.
[Use write_note() to record the conversation details]
```
2. **Referencing existing knowledge**:
```
Human: "Take a look at memory://specs/search"
You: I'll examine that information.
[Use build_context() to gather related information]
[Then read_note() to access specific content]
```
3. **Finding information**:
```
Human: "What were our decisions about auth?"
You: Let me find that information for you.
[Use search() to find relevant notes]
[Then build_context() to understand connections]
```
## Key Things to Remember
1. **Files are Truth**
- All knowledge lives in local files on the user's computer
- Users can edit files outside your interaction
- Changes need to be synced by the user (usually automatic)
- Always verify information is current with `recent_activity()`
2. **Building Context Effectively**
- Start with specific entities
- Follow meaningful relations
- Check recent changes
- Build context incrementally
- Combine related information
3. **Writing Knowledge Wisely**
- Using the same title+folder will overwrite existing notes
- Structure content with clear headings and sections
- Use semantic markup for observations and relations
- Keep files organized in logical folders
## Common Knowledge Patterns
### Capturing Decisions
```markdown
# Coffee Brewing Methods
## Context
I've experimented with various brewing methods including French press, pour over, and espresso.
## Decision
Pour over is my preferred method for light to medium roasts because it highlights subtle flavors and offers more control over the extraction.
## Observations
- [technique] Blooming the coffee grounds for 30 seconds improves extraction #brewing
- [preference] Water temperature between 195-205°F works best #temperature
- [equipment] Gooseneck kettle provides better control of water flow #tools
## Relations
- pairs_with [[Light Roast Beans]]
- contrasts_with [[French Press Method]]
- requires [[Proper Grinding Technique]]
```
### Recording Project Structure
```markdown
# Garden Planning
## Overview
This document outlines the garden layout and planting strategy for this season.
## Observations
- [structure] Raised beds in south corner for sun exposure #layout
- [structure] Drip irrigation system installed for efficiency #watering
- [pattern] Companion planting used to deter pests naturally #technique
## Relations
- contains [[Vegetable Section]]
- contains [[Herb Garden]]
- implements [[Organic Gardening Principles]]
```
### Technical Discussions
```markdown
# Recipe Improvement Discussion
## Key Points
Discussed strategies for improving the chocolate chip cookie recipe.
## Observations
- [issue] Cookies spread too thin when baked at 350°F #texture
- [solution] Chilling dough for 24 hours improves flavor and reduces spreading #technique
- [decision] Will use brown butter instead of regular butter #flavor
## Relations
- improves [[Basic Cookie Recipe]]
- inspired_by [[Bakery-Style Cookies]]
- pairs_with [[Homemade Ice Cream]]
```
### Creating Effective Relations
When creating relations, you can:
1. Reference existing entities by their exact title
2. Create forward references to entities that don't exist yet
```python
# Example workflow for creating notes with effective relations
async def create_note_with_effective_relations():
# Search for existing entities to reference
search_results = await search("travel")
existing_entities = [result.title for result in search_results.primary_results]
# Check if specific entities exist
packing_tips_exists = "Packing Tips" in existing_entities
japan_travel_exists = "Japan Travel Guide" in existing_entities
# Prepare relations section - include both existing and forward references
relations_section = "## Relations\n"
# Existing reference - exact match to known entity
if packing_tips_exists:
relations_section += "- references [[Packing Tips]]\n"
else:
# Forward reference - will be linked when that entity is created later
relations_section += "- references [[Packing Tips]]\n"
# Another possible reference
if japan_travel_exists:
relations_section += "- part_of [[Japan Travel Guide]]\n"
# You can also check recently modified notes to reference them
recent = await recent_activity(timeframe="1 week")
recent_titles = [item.title for item in recent.primary_results]
if "Transportation Options" in recent_titles:
relations_section += "- relates_to [[Transportation Options]]\n"
# Always include meaningful forward references, even if they don't exist yet
relations_section += "- located_in [[Tokyo]]\n"
relations_section += "- visited_during [[Spring 2023 Trip]]\n"
# Now create the note with both verified and forward relations
content = f"""# Tokyo Neighborhood Guide
## Overview
Details about different Tokyo neighborhoods and their unique characteristics.
## Observations
- [area] Shibuya is a busy shopping district #shopping
- [transportation] Yamanote Line connects major neighborhoods #transit
- [recommendation] Visit Shimokitazawa for vintage shopping #unique
- [tip] Get a Suica card for easy train travel #convenience
{relations_section}
"""
result = await write_note(
title="Tokyo Neighborhood Guide",
content=content,
verbose=True
)
# You can check which relations were resolved and which are forward references
if result and 'relations' in result:
resolved = [r['to_name'] for r in result['relations'] if r.get('target_id')]
forward_refs = [r['to_name'] for r in result['relations'] if not r.get('target_id')]
print(f"Resolved relations: {resolved}")
print(f"Forward references that will be resolved later: {forward_refs}")
```
## Error Handling
Common issues to watch for:
1. **Missing Content**
```python
try:
content = await read_note("Document")
except:
# Try search instead
results = await search("Document")
if results and results.primary_results:
# Found something similar
content = await read_note(results.primary_results[0].permalink)
```
2. **Forward References (Unresolved Relations)**
```python
response = await write_note(..., verbose=True)
# Check for forward references (unresolved relations)
forward_refs = []
for relation in response.get('relations', []):
if not relation.get('target_id'):
forward_refs.append(relation.get('to_name'))
if forward_refs:
# This is a feature, not an error! Inform the user about forward references
print(f"Note created with forward references to: {forward_refs}")
print("These will be automatically linked when those notes are created.")
# Optionally suggest creating those entities now
print("Would you like me to create any of these notes now to complete the connections?")
```
3. **Sync Issues**
```python
# If information seems outdated
activity = await recent_activity(timeframe="1 hour")
if not activity or not activity.primary_results:
print("It seems there haven't been recent updates. You might need to run 'basic-memory sync'.")
```
## Best Practices
1. **Proactively Record Context**
- Offer to capture important discussions
- Record decisions, rationales, and conclusions
- Link to related topics
- Ask for permission first: "Would you like me to save our discussion about [topic]?"
- Confirm when complete: "I've saved our discussion to Basic Memory"
2. **Create a Rich Semantic Graph**
- **Add meaningful observations**: Include at least 3-5 categorized observations in each note
- **Create deliberate relations**: Connect each note to at least 2-3 related entities
- **Use existing entities**: Before creating a new relation, search for existing entities
- **Verify wikilinks**: When referencing `[[Entity]]`, use exact titles of existing notes
- **Check accuracy**: Use `search()` or `recent_activity()` to confirm entity titles
- **Use precise relation types**: Choose specific relation types that convey meaning (e.g., "implements" instead of "relates_to")
- **Consider bidirectional relations**: When appropriate, create inverse relations in both entities
3. **Structure Content Thoughtfully**
- Use clear, descriptive titles
- Organize with logical sections (Context, Decision, Implementation, etc.)
- Include relevant context and background
- Add semantic observations with appropriate categories
- Use a consistent format for similar types of notes
- Balance detail with conciseness
4. **Navigate Knowledge Effectively**
- Start with specific searches
- Follow relation paths
- Combine information from multiple sources
- Verify information is current
- Build a complete picture before responding
5. **Help Users Maintain Their Knowledge**
- Suggest organizing related topics
- Identify potential duplicates
- Recommend adding relations between topics
- Offer to create summaries of scattered information
- Suggest potential missing relations: "I notice this might relate to [topic], would you like me to add that connection?"
Built with ♥️ by Basic Machines
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---
title: CLI Reference
type: note
permalink: docs/cli-reference
---
# CLI Reference
Basic Memory provides command line tools for managing your knowledge base. This reference covers the available commands and their options.
## Core Commands
### sync
Keeps files and the knowledge graph in sync:
```bash
# Basic sync
basic-memory sync
# Watch for changes
basic-memory sync --watch
# Sync specific folder
basic-memory sync path/to/folder
```
Options:
- `--watch`: Continuously monitor for changes
- `--verbose`: Show detailed output
- `PATH`: Optional path to sync (defaults to ~/basic-memory)
### import
Imports external knowledge sources:
```bash
# Claude conversations
basic-memory import claude conversations
# Claude projects
basic-memory import claude projects
# ChatGPT history
basic-memory import chatgpt
```
Options:
- `--folder PATH`: Target folder for imported content
- `--overwrite`: Replace existing files
- `--skip-existing`: Keep existing files
### status
Shows system status information:
```bash
# Basic status check
basic-memory status
# Detailed status
basic-memory status --verbose
# JSON output
basic-memory status --json
```
### project
Create multiple projects to manage your knowledge.
```bash
# List all configured projects
basic-memory project list
# Add a new project
basic-memory project add work ~/work-basic-memory
# Set the default project
basic-memory project default work
# Remove a project (doesn't delete files)
basic-memory project remove personal
# Show current project
basic-memory project current
```
> Be sure to restart Claude Desktop after changing projects.
#### Using Projects in Commands
All commands support the `--project` flag to specify which project to use:
```bash
# Sync a specific project
basic-memory --project=work sync
# Run MCP server for a specific project
basic-memory --project=personal mcp
```
You can also set the `BASIC_MEMORY_PROJECT` environment variable:
```bash
BASIC_MEMORY_PROJECT=work basic-memory sync
```
### help
The full list of commands and help for each can be viewed with the `--help` argument.
```
✗ basic-memory --help
Usage: basic-memory [OPTIONS] COMMAND [ARGS]...
Basic Memory - Local-first personal knowledge management system.
╭─ Options ─────────────────────────────────────────────────────────────────────────────────╮
│ --project -p TEXT Specify which project to use │
│ [env var: BASIC_MEMORY_PROJECT] │
│ [default: None] │
│ --version -V Show version information and exit. │
│ --install-completion Install completion for the current shell. │
│ --show-completion Show completion for the current shell, to copy it or │
│ customize the installation. │
│ --help Show this message and exit. │
╰───────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ────────────────────────────────────────────────────────────────────────────────╮
│ sync Sync knowledge files with the database. │
│ status Show sync status between files and database. │
│ reset Reset database (drop all tables and recreate). │
│ mcp Run the MCP server for Claude Desktop integration. │
│ import Import data from various sources │
│ tool Direct access to MCP tools via CLI │
│ project Manage multiple Basic Memory projects │
╰───────────────────────────────────────────────────────────────────────────────────────────╯
```
## Initial Setup
```bash
# Install Basic Memory
uv install basic-memory
# First sync
basic-memory sync
# Start watching mode
basic-memory sync --watch
```
> **Important**: You need to install Basic Memory via `uv` or `pip` to use the command line tools, see [[Getting Started with Basic Memory#Installation]].
## Regular Usage
```bash
# Check status
basic-memory status
# Import new content
basic-memory import claude conversations
# Sync changes
basic-memory sync
# Sync changes continuously
basic-memory sync --watch
```
## Maintenance Tasks
```bash
# Check system status in detail
basic-memory status --verbose
# Full resync of all files
basic-memory sync
# Import updates to specific folder
basic-memory import claude conversations --folder new
```
## Using stdin with Basic Memory's `write_note` Tool
The `write-note` tool supports reading content from standard input (stdin), allowing for more flexible workflows when creating or updating notes in your Basic Memory knowledge base.
### Use Cases
This feature is particularly useful for:
1. **Piping output from other commands** directly into Basic Memory notes
2. **Creating notes with multi-line content** without having to escape quotes or special characters
3. **Integrating with AI assistants** like Claude Code that can generate content and pipe it to Basic Memory
4. **Processing text data** from files or other sources
### Basic Usage
#### Method 1: Using a Pipe
You can pipe content from another command into `write_note`:
```bash
# Pipe output of a command into a new note
echo "# My Note\n\nThis is a test note" | basic-memory tool write-note --title "Test Note" --folder "notes"
# Pipe output of a file into a new note
cat README.md | basic-memory tool write-note --title "Project README" --folder "documentation"
# Process text through other tools before saving as a note
cat data.txt | grep "important" | basic-memory tool write-note --title "Important Data" --folder "data"
```
#### Method 2: Using Heredoc Syntax
For multi-line content, you can use heredoc syntax:
```bash
# Create a note with heredoc
cat << EOF | basic-memory tool write_note --title "Project Ideas" --folder "projects"
# Project Ideas for Q2
## AI Integration
- Improve recommendation engine
- Add semantic search to product catalog
## Infrastructure
- Migrate to Kubernetes
- Implement CI/CD pipeline
EOF
```
#### Method 3: Input Redirection
You can redirect input from a file:
```bash
# Create a note from file content
basic-memory tool write-note --title "Meeting Notes" --folder "meetings" < meeting_notes.md
```
#### Integration with Claude Code
This feature works well with Claude Code in the terminal:
In a Claude Code session, let Claude know he can use the basic-memory tools, then he can execute them via the cli:
```
⏺ Bash(echo "# Test Note from Claude\n\nThis is a test note created by Claude to test the stdin functionality." | basic-memory tool write-note --title "Claude Test Note" --folder "test" --tags "test" --tags "claude")…
  ⎿  # Created test/Claude Test Note.md (23e00eec)
permalink: test/claude-test-note
## Tags
- test, claude
```
## Troubleshooting Common Issues
### Sync Conflicts
If you encounter a file changed during sync error:
1. Check the file referenced in the error message
2. Resolve any conflicts manually
3. Run sync again
### Import Errors
If import fails:
1. Check that the source file is in the correct format
2. Verify permissions on the target directory
3. Use --verbose flag for detailed error information
### Status Issues
If status shows problems:
1. Note any unresolved relations or warnings
2. Run a full sync to attempt automatic resolution
3. Check file permissions if database access errors occur
## Relations
- used_by [[Getting Started with Basic Memory]] (Installation instructions)
- complements [[User Guide]] (How to use Basic Memory)
- relates_to [[Introduction to Basic Memory]] (System overview)
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---
title: Canvas Visualizations
type: note
permalink: docs/canvas
tags:
- visualization
- mapping
- obsidian
---
# Canvas Visualizations
Basic Memory can create visual knowledge maps using Obsidian's Canvas feature. These visualizations help you understand relationships between concepts, map out processes, and visualize your knowledge structure.
## Creating Canvas Visualizations
Ask Claude to create a visualization by describing what you want to map:
```
You: "Create a canvas visualization of my project components and their relationships."
You: "Make a concept map showing the main themes from our discussion about climate change."
You: "Can you make a canvas diagram of the perfect pour over method?"
```
![[Canvas.png]]
## Types of Visualizations
Basic Memory can create several types of visual maps:
### Document Maps
Visualize connections between your notes and documents
### Concept Maps
Create visual representations of ideas and their relationships
### Process Diagrams
Map workflows, sequences, and procedures
### Thematic Analysis
Organize ideas around central themes
### Relationship Networks
Show how different entities relate to each other
## Visualization Sources
Claude can create visualizations based on:
### Documents in Your Knowledge Base
```
You: "Create a canvas showing the connections between my project planning documents"
```
### Conversation Content
```
You: "Make a canvas visualization of the main points we just discussed"
```
### Search Results
```
You: "Find all my notes about psychology and create a visual map of the concepts"
```
### Themes and Relationships
```
You: "Create a visual map showing how different philosophical schools relate to each other"
```
## Visualization Workflow
1. **Request a visualization** by describing what you want to see
2. **Claude creates the canvas file** in your Basic Memory directory
3. **Open the file in Obsidian** to view the visualization
4. **Refine the visualization** by asking Claude for adjustments:
```
You: "Could you reorganize the canvas to group related components together?"
You: "Please add more detail about the connection between these two concepts."
```
## Technical Details
Behind the scenes, Claude:
1. Creates a `.canvas` file in JSON format
2. Adds nodes for each concept or document
3. Creates edges to represent relationships
4. Sets positions for visual clarity
5. Includes any relevant metadata
The resulting file is fully compatible with Obsidian's Canvas feature and can be edited directly in Obsidian.
## Tips for Effective Visualizations
- **Be specific** about what you want to visualize
- **Specify the level of detail** you need
- **Mention the visualization type** you want (concept map, process flow, etc.)
- **Start simple** and ask for refinements
- **Provide context** about what documents or concepts to include
## Relations
- enhances [[Obsidian Integration]] (Using Basic Memory with Obsidian)
- visualizes [[Knowledge Format]] (The structure of your knowledge)
- complements [[User Guide]] (Ways to use Basic Memory)
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---
title: Getting Started with Basic Memory
type: note
permalink: docs/getting-started
---
# Getting Started with Basic Memory
This guide will help you install Basic Memory, configure it with Claude Desktop, and create your first knowledge notes through conversations.
## Installation
### 1. Install Basic Memory
```bash
# Install with uv (recommended)
uv install basic-memory
# Or with pip
pip install basic-memory
```
> **Important**: You need to install Basic Memory using one of the commands above to use the command line tools. The `uvx` command mentioned in the Claude Desktop configuration is only for enabling Claude to access Basic Memory.
### 2. Configure Claude Desktop
To enable Claude to read and write to your knowledge base, edit the Claude Desktop configuration file (usually at `~/Library/Application Support/Claude/claude_desktop_config.json`):
```json
{
"mcpServers": {
"basic-memory": {
"command": "uvx",
"args": [
"basic-memory",
"mcp"
]
}
}
}
```
This configuration uses `uvx` to execute Basic Memory without requiring a full installation in Claude's environment.
### 3. Start the Sync Service
Start the sync service to monitor your files for changes:
```bash
# One-time sync
basic-memory sync
# For continuous monitoring (recommended)
basic-memory sync --watch
```
The `--watch` flag enables automatic detection of file changes, keeping your knowledge base current.
## Creating Your First Knowledge Note
1. **Start a conversation in Claude Desktop** about any topic:
```
You: "Let's talk about coffee brewing methods I've been experimenting with."
```
2. **Have a natural conversation** about the topic
3. **Ask Claude to create a note**:
```
You: "Could you create a note summarizing what we've discussed about coffee brewing?"
```
4. **Claude creates a Markdown file** in your `~/basic-memory` directory
5. **View and edit the file** with any text editor or Obsidian
## Using Special Prompts
Basic Memory includes special prompts that help you start conversations with context from your knowledge base:
### Continue Conversation
To resume a previous topic:
```
You: "Let's continue our conversation about coffee brewing."
```
This prompt triggers Claude to:
1. Search your knowledge base for relevant content about coffee brewing
2. Build context from these documents
3. Resume the conversation with full awareness of previous discussions
### Recent Activity
To see what you've been working on:
```
You: "What have we been discussing recently?"
```
This prompt causes Claude to:
1. Retrieve documents modified in the recent past
2. Summarize the topics and main points
3. Offer to continue any of those discussions
### Search
To find specific information:
```
You: "Find information about pour over coffee methods."
```
Claude will:
1. Search your knowledge base for relevant documents
2. Summarize the key findings
3. Offer to explore specific documents in more detail
## Using Your Knowledge Base
### Referencing Knowledge
In future conversations, reference your existing knowledge:
```
You: "What water temperature did we decide was optimal for coffee brewing?"
```
Or directly reference notes using memory:// URLs:
```
You: "Take a look at memory://coffee-brewing-methods and let's discuss how to improve my technique."
```
### Building On Previous Knowledge
Basic Memory enables continuous knowledge building:
1. **Reference previous discussions** in new conversations
2. **Add to existing notes** through conversations
3. **Create connections** between related topics
4. **Follow relationships** to build comprehensive context
## Importing Existing Conversations
Import your existing AI conversations:
```bash
# From Claude
basic-memory import claude conversations
# From ChatGPT
basic-memory import chatgpt
```
After importing, run `basic-memory sync` to index everything.
## Quick Tips
- Keep `basic-memory sync --watch` running in a terminal window
- Use special prompts (Continue Conversation, Recent Activity, Search) to start contextual discussions
- Build connections between notes for a richer knowledge graph
- Use direct memory:// URLs when you need precise context
- Use git to version control your knowledge base
- Review and edit AI-generated notes for accuracy
## Next Steps
After getting started, explore these areas:
1. **Read the [[User Guide]]** for comprehensive usage instructions
2. **Understand the [[Knowledge Format]]** to learn how knowledge is structured
3. **Set up [[Obsidian Integration]]** for visual knowledge navigation
4. **Learn about [[Canvas]]** visualizations for mapping concepts
5. **Review the [[CLI Reference]]** for command line tools
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---
title: Knowledge Format
type: note
permalink: docs/knowledge-format
tags:
- architecture
- patterns
- knowledge
- design
---
# Knowledge Format
Basic Memory uses standard Markdown with simple semantic patterns to create a knowledge graph. This document details the file structure and patterns used to organize knowledge.
## File-First Architecture
All knowledge in Basic Memory is stored in plain text Markdown files:
- Files are the source of truth for all knowledge
- Changes to files automatically update the knowledge graph
- You maintain complete ownership and control
- Files work with git and other version control systems
- Knowledge persists independently of any AI conversation
## Core Document Structure
Every document uses this basic structure:
```markdown
---
title: Document Title
type: note
tags: [tag1, tag2]
permalink: custom-path
---
# Document Title
Regular markdown content...
## Observations
- [category] Content with #tags (optional context)
## Relations
- relation_type [[Other Document]] (optional context)
```
### Frontmatter
The YAML frontmatter at the top of each file defines essential metadata:
```yaml
---
title: Document Title # Used for linking and references
type: note # Document type
tags: [tag1, tag2] # For organization and searching
permalink: custom-link # Optional custom URL path
---
```
The title is particularly important as it's used to create links between documents.
### Observations
Observations are facts or statements about a topic:
```markdown
## Observations
- [tech] Uses SQLite for storage #database
- [design] Follows local-first architecture #architecture
- [decision] Selected bcrypt for passwords #security (Based on audit)
```
Each observation contains:
- **Category** in [brackets] - classifies the information type
- **Content text** - the main information
- Optional **#tags** - additional categorization
- Optional **(context)** - supporting details
Common categories include:
- `[tech]`: Technical details
- `[design]`: Architecture decisions
- `[feature]`: User capabilities
- `[decision]`: Choices that were made
- `[principle]`: Fundamental concepts
- `[method]`: Approaches or techniques
- `[preference]`: Personal opinions
### Relations
Relations connect documents to form the knowledge graph:
```markdown
## Relations
- implements [[Search Design]]
- depends_on [[Database Schema]]
- relates_to [[User Interface]]
```
You can also create inline references:
```markdown
This builds on [[Core Design]] and uses [[Utility Functions]].
```
Common relation types include:
- `implements`: Implementation of a specification
- `depends_on`: Required dependency
- `relates_to`: General connection
- `inspired_by`: Source of ideas
- `extends`: Enhancement
- `part_of`: Component relationship
- `contains`: Hierarchical relationship
- `pairs_with`: Complementary relationship
## Knowledge Graph
Basic Memory automatically builds a knowledge graph from your document connections:
- Each document becomes a node in the graph
- Relations create edges between nodes
- Relation types add semantic meaning to connections
- Forward references can link to documents that don't exist yet
This graph enables rich context building and navigation across your knowledge base.
## Permalinks and memory:// URLs
Every document in Basic Memory has a unique permalink that serves as its stable identifier:
### How Permalinks Work
- **Automatically assigned**: The system generates a permalink for each document
- **Based on title**: By default, derived from the document title
- **Always unique**: If conflicts exist, the system adds a suffix to ensure uniqueness
- **Stable reference**: Remains the same even if the file moves in the directory structure
- **Used in memory:// URLs**: Forms the basis of the memory:// addressing scheme
You can specify a custom permalink in the frontmatter:
```yaml
---
title: Authentication Approaches
permalink: auth-approaches-2024
---
```
If not specified, one will be generated automatically from the title.
### Using memory:// URLs
The memory:// URL scheme provides a reliable way to reference knowledge:
```
memory://auth-approaches-2024 # Direct access by permalink
memory://Authentication Approaches # Access by title (automatically resolves)
memory://project/auth-approaches # Access by path
```
Memory URLs support pattern matching for more powerful queries:
```
memory://auth* # All documents with permalinks starting with "auth"
memory://*/approaches # All documents with permalinks ending with "approaches"
memory://project/*/requirements # All requirements documents in the project folder
memory://docs/search/implements/* # Follow all implements relations from search docs
```
This addressing scheme ensures content remains accessible even as your knowledge base evolves and files are reorganized.
## File Organization
Organize files in any structure that suits your needs:
```
docs/
architecture/
design.md
patterns.md
features/
search.md
auth.md
```
You can:
- Group by topic in folders
- Use a flat structure with descriptive filenames
- Tag files for easier discovery
- Add custom metadata in frontmatter
The system will build the semantic knowledge graph regardless of how you organize your files.
## Relations
- implemented_by [[User Guide]] (How to work with this format)
- relates_to [[Getting Started with Basic Memory]] (Setup instructions)
- explained_in [[Introduction to Basic Memory]] (Overview of the system)
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---
title: Obsidian Integration
type: note
permalink: docs/obsidian-integration
---
# Obsidian Integration
Basic Memory integrates seamlessly with [Obsidian](https://obsidian.md), providing powerful visualization and navigation capabilities for your knowledge graph.
## Setup
### Creating an Obsidian Vault
1. Download and install [Obsidian](https://obsidian.md)
2. Create a new vault
3. Point it to your Basic Memory directory (~/basic-memory by default)
4. Enable core plugins like Graph View, Backlinks, and Tags
## Visualization Features
### Graph View
Obsidian's Graph View provides a visual representation of your knowledge network:
- Each document appears as a node
- Relations appear as connections between nodes
- Colors can be customized to distinguish types
- Filters let you focus on specific aspects
- Local graphs show connections for individual documents
### Backlinks
Obsidian automatically tracks references between documents:
- View all documents that reference the current one
- See the exact context of each reference
- Navigate easily through connections
- Track how concepts relate to each other
### Tag Explorer
Use tags to organize and filter content:
- View all tags in your knowledge base
- See how many documents use each tag
- Filter documents by tag combinations
- Create hierarchical tag structures
## Knowledge Elements
Basic Memory's knowledge format works natively with Obsidian:
### Wiki Links
```markdown
## Relations
- implements [[Search Design]]
- depends_on [[Database Schema]]
```
These display as clickable links in Obsidian and appear in the graph view.
### Observations with Tags
```markdown
## Observations
- [tech] Using SQLite #database
- [design] Local-first #architecture
```
Tags become searchable and filterable in Obsidian's tag pane.
### Frontmatter
```yaml
---
title: Document Title
type: note
tags: [search, design]
---
```
Frontmatter provides metadata for Obsidian to use in search and filtering.
## Canvas Integration
Basic Memory can create [Obsidian Canvas](https://obsidian.md/canvas) files:
1. Ask Claude to create a visualization:
```
You: "Create a canvas showing the structure of our project components."
```
2. Claude generates a .canvas file in your knowledge base
3. Open the file in Obsidian to view and edit the visual representation
4. Canvas files maintain references to your documents
## Recommended Plugins
These Obsidian plugins work especially well with Basic Memory:
- **Dataview**: Query your knowledge base programmatically
- **Kanban**: Organize tasks from knowledge files
- **Calendar**: View and navigate temporal knowledge
- **Templates**: Create consistent knowledge structures
## Workflow Suggestions
### Daily Notes
```markdown
# 2024-01-21
## Progress
- Updated [[Search Design]]
- Fixed [[Bug Report 123]]
## Notes
- [idea] Better indexing #enhancement
- [todo] Update docs #documentation
## Links
- relates_to [[Current Sprint]]
- updates [[Project Status]]
```
### Project Tracking
```markdown
# Current Sprint
## Tasks
- [ ] Update [[Search]]
- [ ] Fix [[Auth Bug]]
## Tags
#sprint #planning #current
```
## Relations
- enhances [[Introduction to Basic Memory]] (Overview of system)
- relates_to [[Canvas]] (Visual knowledge mapping)
- complements [[User Guide]] (Using Basic Memory)
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---
title: Technical Information
type: note
permalink: docs/technical-information
---
# Technical Information
This document provides technical details about Basic Memory's implementation, licensing, and integration with the Model Context Protocol (MCP).
## Architecture
Basic Memory consists of:
1. **Core Knowledge Engine**: Parses and indexes Markdown files
2. **SQLite Database**: Provides fast querying and search
3. **MCP Server**: Implements the Model Context Protocol
4. **CLI Tools**: Command-line utilities for management
5. **Sync Service**: Monitors file changes and updates the database
The system follows a file-first architecture where all knowledge is represented in standard Markdown files and the database serves as a secondary index.
## Model Context Protocol (MCP)
Basic Memory implements the [Model Context Protocol](https://github.com/modelcontextprotocol/spec), an open standard for enabling AI models to access external tools:
- **Standardized Interface**: Common protocol for tool integration
- **Tool Registration**: Basic Memory registers as a tool provider
- **Asynchronous Communication**: Enables efficient interaction with AI models
- **Standardized Schema**: Structured data exchange format
Integration with Claude Desktop uses the MCP to grant Claude access to your knowledge base through a set of specialized tools that search, read, and write knowledge.
## Licensing
Basic Memory is licensed under the [GNU Affero General Public License v3.0 (AGPL-3.0)](https://www.gnu.org/licenses/agpl-3.0.en.html):
- **Free Software**: You can use, study, share, and modify the software
- **Copyleft**: Derivative works must be distributed under the same license
- **Network Use**: Network users must be able to receive the source code
- **Commercial Use**: Allowed, subject to license requirements
The AGPL license ensures Basic Memory remains open source while protecting against proprietary forks.
## Source Code
Basic Memory is developed as an open-source project:
- **GitHub Repository**: [https://github.com/basicmachines-co/basic-memory](https://github.com/basicmachines-co/basic-memory)
- **Issue Tracker**: Report bugs and request features on GitHub
- **Contributions**: Pull requests are welcome following the contributing guidelines
- **Documentation**: Source for this documentation is also available in the repository
## Data Storage and Privacy
Basic Memory is designed with privacy as a core principle:
- **Local-First**: All data remains on your local machine
- **No Cloud Dependency**: No remote servers or accounts required
- **Telemetry**: Optional and disabled by default
- **Standard Formats**: All data is stored in standard file formats you control
## Implementation Details
### Entity Model
Basic Memory's core data model consists of:
- **Entities**: Documents in your knowledge base
- **Observations**: Facts or statements about entities
- **Relations**: Connections between entities
- **Tags**: Additional categorization for entities and observations
The system parses Markdown files to extract this structured information while preserving the human-readable format.
### Sync Process
The sync process:
1. Detects changes to files in the knowledge directory
2. Parses modified files to extract structured data
3. Updates the SQLite database with changes
4. Resolves forward references when new entities are created
5. Updates the search index for fast querying
### Search Engine
The search functionality:
1. Uses a combination of full-text search and semantic matching
2. Indexes observations, relations, and content
3. Supports wildcards and pattern matching in memory:// URLs
4. Traverses the knowledge graph to follow relationships
5. Ranks results by relevance to the query
## Relations
- relates_to [[Introduction to Basic Memory]] (System overview)
- relates_to [[CLI Reference]] (Command line tools)
- implements [[Knowledge Format]] (File structure and format)
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---
title: User Guide
type: note
permalink: docs/user-guide
---
# User Guide
This guide explains how to effectively use Basic Memory in your daily workflow, from creating knowledge through conversations to building a rich semantic network.
## Basic Memory Workflow
Using Basic Memory follows a natural cycle:
1. **Have conversations** with AI assistants like Claude
2. **Capture knowledge** in Markdown files
3. **Build connections** between pieces of knowledge
4. **Reference your knowledge** in future conversations
5. **Edit files directly** when needed
6. **Sync changes** automatically
## Creating Knowledge
### Through Conversations
To create knowledge during conversations with Claude:
```
You: We've covered several authentication approaches. Could you create a note summarizing what we've discussed?
Claude: I'll create a note summarizing our authentication discussion.
```
This creates a Markdown file in your `~/basic-memory` directory with semantic markup.
### Direct File Creation
You can create files directly:
1. Create a new Markdown file in your `~/basic-memory` directory
2. Add frontmatter with title, type, and optional tags
3. Structure content with observations and relations
4. Save the file
5. Run `basic-memory sync` if not in watch mode
## Using Special Prompts
Basic Memory includes several special prompts that help you leverage your knowledge base more effectively. In apps like Claude Desktop, these prompts trigger specific tools to search and analyze your knowledge base.
### Continue Conversation
When you want to pick up where you left off on a topic:
```
You: Let's continue our conversation about authentication systems.
```
Behind the scenes:
- Claude searches your knowledge base for content about "authentication systems"
- It retrieves relevant documents and their relations
- It analyzes the context to understand where you left off
- It builds a comprehensive picture of what you've previously discussed
- It can then resume the conversation with all that context
This is particularly useful when:
- Starting a new session days or weeks after your last discussion
- Switching between multiple ongoing projects
- Building on previous work without repeating yourself
### Recent Activity
To get an overview of what you've been working on:
```
You: What have we been discussing recently?
```
Behind the scenes:
- Claude retrieves documents modified recently
- It analyzes patterns and themes
- It summarizes the key topics and changes
- It offers to continue working on any of those topics
This is useful for:
- Coming back after a break
- Getting a quick reminder of ongoing projects
- Deciding what to work on next
### Search
To find specific information in your knowledge base:
```
You: Find information about JWT authentication in my notes.
```
Behind the scenes:
- Claude performs a semantic search for "JWT authentication"
- It retrieves and ranks the most relevant documents
- It summarizes the key findings
- It offers to explore specific areas in more detail
This is useful for:
- Finding specific information quickly
- Exploring what you know about a topic
- Starting work on an existing topic
### Example
Choose "Continue Conversation"
![[prompt 1.png|500]]
Enter a topic
![[prompt2.png|500]]
Give instructions
![[prompt3.png|500]]
Claude can build context from the supplied topic.
![[prompt4.png|500]]
## Searching Your Knowledge Base
Basic Memory provides multiple ways to search and explore your knowledge base:
### Natural Language Search
The simplest way to search is to ask Claude directly:
```
You: What do I know about authentication methods?
```
Claude will search your knowledge base semantically and return relevant information.
### Search Prompt
Use the dedicated search prompt for more focused searches:
```
You: Search for "JWT authentication"
```
This triggers a specialized search that returns precise results with document titles, relevant excerpts, and offers to explore specific documents.
### Boolean Search
For more precise searches, use boolean operators to refine your queries:
```
You: Search for "authentication AND OAuth NOT basic"
```
Basic Memory supports standard boolean operators:
- **AND**: Find documents containing both terms
```
You: Search for "python AND flask"
```
This finds documents containing both "python" and "flask"
- **OR**: Find documents containing either term
```
You: Search for "python OR javascript"
```
This finds documents containing either "python" or "javascript"
- **NOT**: Exclude documents containing specific terms
```
You: Search for "python NOT django"
```
This finds documents containing "python" but excludes those containing "django"
- **Grouping with parentheses**: Control operator precedence
```
You: Search for "(python OR javascript) AND web"
```
This finds documents about web development that mention either Python or JavaScript
Boolean search is particularly useful for:
- Narrowing down results in large knowledge bases
- Finding specific combinations of concepts
- Excluding irrelevant content from search results
- Creating complex queries for precise information retrieval
### Memory URL Pattern Matching
For advanced searches, use memory:// URL patterns with wildcards:
```
You: Look at memory://auth* and summarize all authentication approaches.
```
Pattern matching supports:
- **Wildcards**: `memory://auth*` matches all permalinks starting with "auth"
- **Path patterns**: `memory://project/*/auth` matches auth documents in any project subfolder
- **Relation traversal**: `memory://auth-system/implements/*` finds all documents that implement the auth system
### Combining Search with Context Building
The most powerful searches build comprehensive context by following relationships:
```
You: Search for JWT authentication and then follow all implementation relations.
```
This builds a complete picture by:
1. Finding documents about JWT authentication
2. Following implementation relationships from those documents
3. Building a complete picture of how JWT is implemented across your system
### Search Best Practices
For effective searching:
1. **Be specific** with search terms and phrases
2. **Use boolean operators** to refine searches and find precise information
3. **Use technical terms** when searching for technical content
4. **Follow up** on search results by asking for more details about specific documents
5. **Combine approaches** by starting with search and then using memory:// URLs for precision
6. **Use relation traversal** to explore connected concepts after finding initial documents
## Referencing Knowledge
### Using memory:// URLs
Reference specific knowledge directly:
```
You: Please look at memory://authentication-approaches and suggest which approach would be best for our mobile app.
```
### Natural Language References
Reference knowledge conversationally:
```
You: What did we decide about authentication for the project?
```
### Advanced References
Follow connections across your knowledge graph:
```
You: Look at memory://project-architecture and check related documents to give me a complete picture.
```
## Working with Files
### File Location and Organization
By default, Basic Memory stores files in `~/basic-memory`:
- Browse this directory in your file explorer
- Organize files into subfolders
- Use git for version control
### File Format
Each knowledge file follows this structure:
```markdown
---
title: Authentication Approaches
type: note
tags: [security, architecture]
permalink: authentication-approaches
---
# Authentication Approaches
A comparison of authentication methods.
## Observations
- [approach] JWT provides stateless authentication #security
- [limitation] Session tokens require server-side storage #infrastructure
## Relations
- implements [[Security Requirements]]
- affects [[User Login Flow]]
```
### Editing Files
Modify files in any text editor:
1. Open the file in your preferred editor
2. Make changes to content, observations, or relations
3. Save the file
4. Basic Memory detects changes automatically when running in watch mode
## Building a Knowledge Graph
The value of Basic Memory comes from connections between pieces of knowledge.
### Creating Relations
When creating or editing notes, build connections:
```markdown
## Relations
- implements [[Security Requirements]]
- depends_on [[User Authentication]]
```
Relations can be:
- Hierarchical (part_of, contains)
- Directional (implements, depends_on)
- Associative (relates_to, similar_to)
- Temporal (precedes, follows)
Relations are also created via regular wiki-link style links within the body text.
### Forward References
Reference documents that don't exist yet:
```markdown
- will_impact [[Future Feature]]
```
These references resolve automatically when you create the referenced document.
## Conversation Continuity
Basic Memory maintains context across different conversations.
### Starting New Sessions with Context
When starting a new conversation with Claude, you can:
1. **Use special prompts** like "Continue conversation about..." or "What were we working on?"
2. **Reference specific documents** with memory:// URLs
3. **Ask about recent work** with "What have we been discussing recently?"
4. **Search for specific topics** with "Find information about..."
### Long-Term Projects
Maintain context for complex projects over time:
1. **Document key decisions** as you make them
2. **Create relationships** between project components
3. **Reference past decisions** when implementing features
4. **Update documentation** as the project evolves
### Tips for Effective Continuity
1. **Be specific about topics** when continuing a conversation
2. **Reference documents directly** with memory:// URLs for precision
3. **Create summary notes** after important discussions
4. **Update existing notes** rather than creating duplicates
5. **Build robust connections** between related topics
## Advanced Features
### Importing External Knowledge
Import existing conversations:
```bash
# From Claude
basic-memory import claude conversations
# From ChatGPT
basic-memory import chatgpt
```
After importing, run `basic-memory sync` to index everything.
### Obsidian Integration
Use with [Obsidian](https://obsidian.md):
1. Point Obsidian to your `~/basic-memory` directory
2. Use Obsidian's graph view to visualize your knowledge network
3. All changes sync back to Basic Memory
### Canvas Visualizations
Create visual knowledge maps:
```
You: Could you create a canvas visualization of our project components?
```
This generates an Obsidian canvas file showing the relationships between concepts.
### Advanced Memory URI Patterns
Use wildcards and patterns:
```
You: Review memory://project/*/requirements to summarize all project requirements.
```
## Command Line Interface
### Sync Commands
```bash
# One-time sync
basic-memory sync
# Watch for changes
basic-memory sync --watch
```
### Status and Information
```bash
# Check system status
basic-memory status
# View CLI help
basic-memory --help
```
### Import Commands
```bash
# Import from Claude
basic-memory import claude conversations
# Import from ChatGPT
basic-memory import chatgpt
```
## Multiple Projects
Basic Memory supports managing multiple separate knowledge bases through projects. This feature allows you to maintain
separate knowledge graphs for different purposes (e.g., personal notes, work projects, research topics).
Basic Memory keeps a list of projects in a config file: ` ~/.basic-memory/config.json`
### Managing Projects
```bash
# List all configured projects
basic-memory project list
# Add a new project
basic-memory project add work ~/work-basic-memory
# Set the default project
basic-memory project default work
# Remove a project (doesn't delete files)
basic-memory project remove personal
# Show current project
basic-memory project current
```
### Using Projects in Commands
All commands support the `--project` flag to specify which project to use:
```bash
# Sync a specific project
basic-memory --project=work sync
# Run MCP server for a specific project
basic-memory --project=personal mcp
```
You can also set the `BASIC_MEMORY_PROJECT` environment variable:
```bash
BASIC_MEMORY_PROJECT=work basic-memory sync
```
### Project Isolation
Each project maintains:
- Its own collection of markdown files in the specified directory
- A separate SQLite database for that project
- Complete knowledge graph isolation from other projects
## Workflow Tips
1. Run sync in watch mode for automatic updates
2. Use git for version control of your knowledge base
3. Review and edit AI-created content for accuracy
4. Periodically organize and refine your knowledge structure
5. Build rich connections between related ideas
6. Use forward references to plan future documentation
7. Start conversations with special prompts to leverage existing knowledge
## Troubleshooting
### Sync Issues
If changes aren't showing up:
1. Verify `basic-memory sync --watch` is running
2. Run `basic-memory status` to check system state
3. Try a manual sync with `basic-memory sync`
### Missing Content
If content isn't found:
1. Check the exact path and permalink
2. Try searching with more general terms
3. Verify the file exists in your knowledge base
### Relation Problems
If relations aren't working:
1. Ensure exact title matching in [[WikiLinks]]
2. Check for typos in relation types
3. Verify both documents exist
## Relations
- implements [[Knowledge Format]] (How knowledge is structured)
- relates_to [[Getting Started with Basic Memory]] (Setup and first steps)
- relates_to [[Canvas]] (Creating visual knowledge maps)
- relates_to [[CLI Reference]] (Command line tools)
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---
title: Introduction to Basic Memory
type: docs
permalink: docs/introduction
tags:
- documentation
- index
- overview
---
# BASIC MEMORY
Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations
with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and
ownership of your data.
## Core Functions
Basic Memory connects you and AI assistants through shared knowledge:
1. **Captures knowledge** from natural conversations with AI assistants
2. **Structures information** using simple semantic patterns in Markdown
3. **Enables knowledge reuse** across different conversations and sessions
4. **Maintains persistence** through local files you control completely
Both you and AI assistants like Claude can read from and write to the same knowledge base, creating a continuous
learning environment where each conversation builds upon previous ones.
![[Obsidian-CoffeeKnowledgeBase-examples-overlays.gif]]
## Technical Architecture
Basic Memory uses:
- **Files as the source of truth** - Everything is stored in plain Markdown files
- **Git-compatible storage** - All knowledge can be versioned, branched, and merged
- **Local SQLite database** - For fast indexing and searching only (not primary storage)
- **Memory:// URI scheme** - For precise knowledge referencing and navigation
- **Model Context Protocol (MCP)** - For seamless AI assistant integration
## Knowledge Structure
Knowledge in Basic Memory is organized as a semantic graph:
1. **Entities** - Distinct concepts represented by Markdown documents
2. **Observations** - Categorized facts and information about entities
3. **Relations** - Connections between entities that form the knowledge graph
This structure emerges from simple text patterns in standard Markdown:
```markdown
---
title: Coffee Brewing Methods
type: note
permalink: coffee/coffee-brewing-methods
tags:
- '#coffee'
- '#brewing'
- '#methods'
- '#demo'
---
# Coffee Brewing Methods
An exploration of different coffee brewing techniques, their characteristics, and how they affect flavor extraction.
## Overview
Coffee brewing is both an art and a science. Different brewing methods extract different compounds from coffee beans,
resulting in unique flavor profiles, body, and mouthfeel. The key variables in any brewing method are:
- Grind size
- Water temperature
- Brew time
- Coffee-to-water ratio
- Agitation/turbulence
## Observations
- [principle] Coffee extraction follows a predictable pattern: acids extract first, then sugars, then bitter compounds
#extraction
- [method] Pour over methods generally produce cleaner, brighter cups with more distinct flavor notes #clarity
## Relations
- requires [[Proper Grinding Technique]]
- affects [[Flavor Extraction]]
```
Becomes
```json
{
"entities": [
{
"permalink": "coffee/coffee-brewing-methods",
"title": "Coffee Brewing Methods",
"file_path": "Coffee Notes/Coffee Brewing Methods.md",
"entity_type": "note",
"entity_metadata": {
"title": "Coffee Brewing Methods",
"type": "note",
"permalink": "coffee/coffee-brewing-methods",
"tags": "['#coffee', '#brewing', '#methods', '#demo']"
},
"checksum": "bfa32a0f23fa124b53f0694c344d2788b0ce50bd090b55b6d738401d2a349e4c",
"content_type": "text/markdown",
"observations": [
{
"category": "principle",
"content": "Coffee extraction follows a predictable pattern: acids extract first, then sugars, then bitter compounds #extraction",
"tags": [
"extraction"
],
"permalink": "coffee/coffee-brewing-methods/observations/principle/coffee-extraction-follows-a-predictable-pattern-acids-extract-first-then-sugars-then-bitter-compounds-extraction"
},
{
"category": "method",
"content": "Pour over methods generally produce cleaner, brighter cups with more distinct flavor notes #clarity",
"tags": [
"clarity"
],
"permalink": "coffee/coffee-brewing-methods/observations/method/pour-over-methods-generally-produce-cleaner-brighter-cups-with-more-distinct-flavor-notes-clarity"
}
],
"relations": [
{
"from_id": "coffee/coffee-bean-origins",
"to_id": "coffee/coffee-brewing-methods",
"relation_type": "pairs_with",
"context": null,
"permalink": "coffee/coffee-bean-origins/pairs-with/coffee/coffee-brewing-methods",
"to_name": "Coffee Brewing Methods"
},
{
"from_id": "coffee/flavor-extraction",
"to_id": "coffee/coffee-brewing-methods",
"relation_type": "affected_by",
"context": null,
"permalink": "coffee/flavor-extraction/affected-by/coffee/coffee-brewing-methods",
"to_name": "Coffee Brewing Methods"
}
],
"created_at": "2025-03-06T14:01:23.445071",
"updated_at": "2025-03-06T13:34:48.563606"
}
]
}
```
Basic Memory understands how to build context via its semantic graph.
## User Control and File Management
Basic Memory gives you complete control over your knowledge:
- **Local-first storage** - All knowledge lives on your computer
- **Standard file formats** - Plain Markdown compatible with any editor
- **Directory organization** - Knowledge stored in `~/basic-memory` by default
- **Version control ready** - Use git for history, branching, and collaboration
- **Edit anywhere** - Modify files with any text editor or Obsidian
Changes to files automatically update the knowledge graph, and AI assistants can see your edits in future conversations.
## Documentation Map
Continue exploring Basic Memory with these guides:
- Installation and setup [[Getting Started with Basic Memory]]
- Comprehensive usage instructions [[User Guide]]
- Detailed explanation of knowledge structure [[Knowledge Format]]
- Reference for AI assistants using Basic Memory [[AI Assistant Guide]]
- Technical implementation details [[Technical Information]]
- Command line tool reference [[CLI Reference]]
- Obsidian integration guide [[Obsidian Integration]]
- Canvas visualization guide [[Canvas]]
## Next Steps
Start with the [[Getting Started with Basic Memory]] guide to install Basic Memory and configure it with your AI
assistant.
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@@ -0,0 +1,83 @@
---
title: Brewing Equipment
type: note
permalink: coffee/brewing-equipment
tags:
- '#coffee'
- '#equipment'
- '#gear'
- '#brewing'
- '#demo'
---
# Brewing Equipment
Essential tools and equipment for brewing coffee, their characteristics, and how they affect the brewing process.
## Overview
The equipment used to brew coffee plays a crucial role in determining the final cup quality. From grinders to brewers to kettles, each piece of equipment contributes to different aspects of the brewing process.
## Observations
- [principle] Equipment quality often has a bigger impact on consistency than on absolute quality potential #quality
- [principle] Good grind consistency is the most important technical factor in extraction quality #grind
- [investment] A good burr grinder is often the most important investment for improving home coffee #gear
- [technique] Equipment maintenance and cleaning significantly impact flavor consistency over time #maintenance
## Grinders
- [equipment] Burr grinders crush beans between two abrasive surfaces for more consistent particle size #grinders
- [equipment] Blade grinders chop beans unevenly, leading to inconsistent extraction #grinders
- [equipment] Flat burr grinders produce very consistent particle size but generate more heat #burrs
- [equipment] Conical burr grinders create slightly less uniform grounds but with less heat and noise #burrs
- [feature] Grind adjustment mechanisms range from stepped to stepless for different precision levels #adjustment
- [feature] Retention (grounds trapped in grinder) affects dose consistency and freshness #retention
- [price] Hand grinders offer excellent value, with models like Timemore C2 and 1Zpresso JX providing excellent results around $100-150 #budget
- [price] Entry-level electric burr grinders like Baratza Encore start around $170 but provide significant improvement over blade grinders #value
## Brewers
### Pour Over Brewers
- [equipment] Hario V60 uses a conical design with spiral ridges to control flow rate #pourover
- [equipment] Kalita Wave has a flat bottom with three small holes for more consistent extraction #pourover
- [equipment] Chemex combines brewer and server with thick proprietary filters for ultra-clean cup #pourover
- [material] Ceramic brewers retain heat better than plastic but are more fragile #materials
- [material] Glass brewers provide neutral flavor but less heat retention #materials
- [material] Plastic brewers are inexpensive, durable, and surprisingly good for heat retention #materials
### Immersion Brewers
- [equipment] French Press uses a metal mesh to separate grounds, allowing oils and fine particles to pass #immersion
- [equipment] AeroPress uses pressure and paper filter for clean, versatile brewing #immersion
- [equipment] Clever Dripper combines immersion and drip methods with a valve mechanism #hybrid
- [material] Glass French presses look elegant but break easily and have poor heat retention #materials
- [material] Stainless steel or ceramic French presses offer better durability and heat retention #materials
### Pressure Brewers
- [equipment] Espresso machines use 9 bars of pressure, requiring significant investment for good results #espresso
- [equipment] Moka pot uses steam pressure for strong, concentrated coffee at affordable price #moka
- [equipment] Manual lever machines like Flair or Robot provide espresso-style coffee with manual control #manual_espresso
## Kettles
- [equipment] Gooseneck kettles provide precision pouring control essential for pour over methods #kettles
- [feature] Variable temperature kettles allow precise temperature control for different roast levels #temp_control
- [feature] Flow restrictors can help beginners maintain consistent pour rates #pour_control
- [material] Electric kettles offer convenience and temperature stability #convenience
- [material] Stovetop kettles may be more durable but offer less temperature control #durability
## Accessories
- [equipment] Coffee scale with 0.1g precision helps maintain consistent ratios #measurement
- [equipment] Timer ensures consistent extraction times #consistency
- [equipment] Quality filters significantly impact flavor clarity and body #filters
- [equipment] Storage containers with one-way valves help preserve bean freshness #storage
- [equipment] Blind shaker or dosing cup reduces grinder mess and improves workflow #workflow
## Relations
- improves [[Coffee Brewing Methods]]
- affects [[Flavor Extraction]]
- requires [[Proper Maintenance]]
- enhances [[Home Coffee Setup]]
- part_of [[Coffee Knowledge Base]]
@@ -0,0 +1,78 @@
---
title: Coffee Bean Origins
type: note
permalink: coffee/coffee-bean-origins
tags:
- '#coffee'
- '#origins'
- '#beans'
- '#regions'
- '#demo'
---
# Coffee Bean Origins
An exploration of coffee-growing regions around the world and how geography, climate, and processing methods affect flavor profiles.
## Overview
Coffee beans are grown in various regions around the world, primarily in what's known as the "Coffee Belt" - the area between the Tropics of Cancer and Capricorn. The flavor characteristics of coffee beans are influenced by:
- Geographic region and climate
- Altitude
- Soil composition
- Variety of coffee plant
- Processing method
- Harvest and sorting practices
## Observations
- [principle] Higher altitude generally produces harder, denser beans with more complex acidity #altitude
- [region] Ethiopian beans often feature bright, fruity notes with floral aromatics #ethiopia
- [region] Colombian coffee typically offers balanced acidity with caramel sweetness and nutty undertones #colombia
- [region] Guatemalan coffee presents complex acidity with chocolate notes and sometimes spice characteristics #guatemala
- [region] Brazilian coffee tends toward nutty, chocolate notes with lower acidity and fuller body #brazil
- [region] Kenyan coffee is known for bright, wine-like acidity and berry or citrus notes #kenya
- [processing] Natural (dry) processing tends to create fruitier, more fermented flavors #processing
- [processing] Washed (wet) processing generally results in cleaner, brighter cups with more clarity #processing
- [processing] Honey processing creates a middle ground with some fruity notes while maintaining clarity #processing
- [factor] Shade-grown coffee typically develops more slowly, resulting in more complex flavors #cultivation
- [factor] Soil volcanic soil often imparts distinctive mineral characteristics to coffee #terroir
- [variety] Gesha/Geisha variety is known for exceptional floral and tea-like qualities #varieties
- [variety] Bourbon varieties often feature sweet, complex cup profiles #varieties
- [variety] Robusta beans have higher caffeine content but generally less complex flavor than Arabica #varieties
## Major Growing Regions
- [africa] Ethiopian coffees: Yirgacheffe, Sidamo, Harrar regions each with distinctive profiles #ethiopia
- [africa] Kenyan coffees: Often categorized by grade (AA, AB, etc.) based on bean size #kenya
- [americas] Colombian regions: Huila, Nariño, Antioquia each with unique characteristics #colombia
- [americas] Central American producers: Guatemala, Costa Rica, Panama known for balanced profiles #central_america
- [americas] Brazilian regions: Cerrado, Sul de Minas, Mogiana with varying profiles #brazil
- [asia] Indonesian islands: Sumatra, Java, Sulawesi producing earthy, full-bodied coffees #indonesia
- [asia] Vietnamese coffee: World's largest Robusta producer, often used in blends and commercial coffee #vietnam
## Processing Methods
- [natural] Beans dried inside the fruit, creating fruity, fermented notes and heavier body #processing
- [washed] Fruit removed before drying, resulting in cleaner cup with more pronounced acidity #processing
- [honey] Some fruit mucilage left on during drying, creates balanced sweetness and body #processing
- [wet-hulled] Unique to Indonesia, creates earthy, herbal, low-acid profiles #processing
- [experimental] Anaerobic fermentation, wine-yeast inoculation, and other newer methods #innovation
## Tasting Notes by Region
- [ethiopia] Blueberry, jasmine, bergamot, stone fruit, citrus #flavor_notes
- [kenya] Blackcurrant, tomato, tropical fruit, wine-like acidity #flavor_notes
- [colombia] Caramel, nuts, red apple, chocolate, balanced acidity #flavor_notes
- [guatemala] Chocolate, spice, green apple, balanced #flavor_notes
- [brazil] Nuts, chocolate, low acidity, full body #flavor_notes
- [indonesia] Earthy, herbal, spice, cedar, full body, low acidity #flavor_notes
## Relations
- influences [[Flavor Extraction]]
- pairs_with [[Coffee Brewing Methods]]
- affects [[Tasting Notes]]
- relates_to [[Specialty Coffee]]
- part_of [[Coffee Knowledge Base]]
@@ -0,0 +1,70 @@
---
title: Coffee Brewing Methods
type: note
permalink: coffee/coffee-brewing-methods
tags:
- '#coffee'
- '#brewing'
- '#methods'
- '#demo'
---
# Coffee Brewing Methods
An exploration of different coffee brewing techniques, their characteristics, and how they affect flavor extraction.
## Overview
Coffee brewing is both an art and a science. Different brewing methods extract different compounds from coffee beans, resulting in unique flavor profiles, body, and mouthfeel. The key variables in any brewing method are:
- Grind size
- Water temperature
- Brew time
- Coffee-to-water ratio
- Agitation/turbulence
## Observations
- [principle] Coffee extraction follows a predictable pattern: acids extract first, then sugars, then bitter compounds #extraction
- [method] Pour over methods generally produce cleaner, brighter cups with more distinct flavor notes #clarity
- [method] Immersion methods like French press create fuller body and more rounded flavors #body
- [technique] Water at 195-205°F (90-96°C) extracts optimal flavor compounds for most brewing methods #temperature
- [technique] Grind size directly correlates with ideal extraction time (finer = shorter, coarser = longer) #grind
- [preference] Medium-light roasts often showcase more origin characteristics in pour over methods #roast
- [equipment] Burr grinders produce more consistent particle size than blade grinders, resulting in more even extraction #gear
- [ratio] 1:15 to 1:17 coffee-to-water ratio (by weight) works well for most brew methods #brewing
- [science] Different brewing temperatures extract different chemical compounds from the beans #chemistry
- [technique] Bloom phase (pre-infusion with small amount of water) allows CO2 to escape and improves extraction #bloom
## Pour Over Methods
- [method] V60 produces very clean cup with excellent clarity of flavor #pourover
- [method] Chemex uses thicker filter paper, resulting in even cleaner cup with fewer oils #pourover
- [method] Kalita Wave provides more consistent extraction due to flat bottom design #pourover
- [technique] Concentric circular pouring pattern ensures even saturation of grounds #technique
- [timing] Most pour over methods complete in 2:30-3:30 total brew time #brewing
## Immersion Methods
- [method] French Press creates full-bodied cup with rich mouthfeel due to metal filter allowing oils to pass #immersion
- [method] AeroPress is versatile, capable of producing both espresso-like and filter-style coffee #immersion
- [method] Cold brew uses time instead of heat to extract, resulting in lower acidity #immersion
- [technique] French press ideal steep time is 4-5 minutes before plunging #timing
- [technique] AeroPress inverted method prevents dripping during extraction phase #technique
## Pressure Methods
- [method] Espresso uses 9 bars of pressure to force water through finely ground coffee #pressure
- [method] Moka pot uses steam pressure to push water through grounds, creating strong, concentrated coffee #pressure
- [technique] Espresso requires very fine grind, almost powder-like consistency #grind
- [timing] Espresso shots typically extract in 25-30 seconds #timing
- [principle] Pressure methods can extract compounds that aren't soluble in regular brewing methods #extraction
## Relations
- requires [[Proper Grinding Technique]]
- affects [[Flavor Extraction]]
- pairs_with [[Coffee Bean Origins]]
- uses [[Brewing Equipment]]
- influences [[Tasting Notes]]
- part_of [[Coffee Knowledge Base]]
@@ -0,0 +1,89 @@
---
title: Coffee Flavor Map
type: note
permalink: coffee/coffee-flavor-map
tags:
- '#coffee'
- '#visualization'
- '#canvas'
- '#demo'
---
# Coffee Flavor Map
A visual mapping of coffee flavor attributes, brewing methods, and their relationships. This note describes a canvas visualization that could be generated to demonstrate Basic Memory's visualization capabilities.
## Overview
The Coffee Flavor Map provides a visual representation of how different brewing methods, coffee origins, and equipment choices affect flavor outcomes. This canvas visualization helps users understand the complex relationships in coffee brewing and tasting.
## Canvas Visualization Elements
### Core Nodes
- **Flavor Attributes**: Acidity, Sweetness, Body, Clarity, Bitterness, Complexity
- **Brewing Methods**: Pour Over, French Press, AeroPress, Espresso, Moka Pot, Cold Brew
- **Origin Regions**: Ethiopia, Kenya, Colombia, Brazil, Guatemala, Indonesia
- **Equipment Elements**: Grinder Quality, Water Temperature, Brewing Device, Filter Type
### Node Connections
- Lines connecting brewing methods to their typical flavor outcomes
- Arrows showing how equipment choices affect extraction variables
- Connections between origins and their characteristic flavor profiles
- Highlighting of optimal brewing methods for different origins
### Visual Organization
- Flavor outcomes in the center
- Brewing methods on the left side
- Origins on the right side
- Equipment variables at the bottom
- Color coding by category (methods, origins, equipment, flavors)
## Using This Visualization
### For Coffee Exploration
- Identify which brewing methods might highlight the characteristics you prefer
- See which origins naturally pair well with your preferred brewing method
- Understand how equipment changes can modify flavor outcomes
- Visualize the complex interplay between all coffee variables
### As a Basic Memory Demo
- Demonstrates Canvas visualization capabilities
- Shows how relations can be visually mapped
- Illustrates complex knowledge organization
- Provides an intuitive way to navigate coffee knowledge
## How To Generate This Canvas
In a conversation with Claude, you could request:
```
Please create a canvas visualization mapping the relationships between coffee brewing methods, origins, and flavor outcomes. Show how different equipment and techniques influence extraction and resulting flavor profiles.
```
This would generate a `.canvas` file in your Basic Memory directory that could be opened with Obsidian for an interactive visualization of these coffee relationships.
## Example Visualization Snippets
### Pour Over Method Node
- Connected to: High Clarity, Bright Acidity, Medium Body
- Best pairs with: Ethiopian and Kenyan beans
- Equipment dependencies: Gooseneck Kettle, Paper Filter, Burr Grinder
### Ethiopian Coffee Node
- Characteristic flavors: Floral, Fruity, Bright
- Best brewing methods: Pour Over, AeroPress
- Challenging with: French Press (loses clarity of delicate notes)
### Grind Size Node
- Affects: Extraction Rate, Flavor Balance
- Fine grind increases: Extraction Speed, Surface Area
- Coarse grind increases: Flow Rate, Reduces Bitter Compounds
## Relations
- visualizes [[Coffee Knowledge Base]]
- relates_to [[Coffee Brewing Methods]]
- relates_to [[Coffee Bean Origins]]
- relates_to [[Flavor Extraction]]
- relates_to [[Tasting Notes]]
- demonstrates [[Canvas]]
@@ -0,0 +1,73 @@
---
title: Coffee Knowledge Base
type: note
permalink: coffee/coffee-knowledge-base
tags:
- '#coffee'
- '#index'
- '#demo'
- '#knowledge'
---
# Coffee Knowledge Base
A comprehensive collection of coffee knowledge, from bean origins to brewing methods to tasting notes. This knowledge base demonstrates Basic Memory's ability to organize and connect information in a meaningful way.
## Overview
This Coffee Knowledge Base captures key information about coffee, structured with semantic observations and relations that connect different aspects of coffee knowledge. It serves as both a useful reference for coffee enthusiasts and a demonstration of how Basic Memory organizes information.
## Key Topics
### Core Coffee Knowledge
- [[Coffee Brewing Methods]] - Different techniques for preparing coffee
- [[Coffee Bean Origins]] - Where coffee comes from and how region affects flavor
- [[Brewing Equipment]] - Tools and devices used to prepare coffee
- [[Flavor Extraction]] - The science of dissolving flavor compounds from coffee
- [[Tasting Notes]] - How to taste and describe coffee flavors
### Brewing Techniques
- Proper grinding is fundamental to good extraction
- Water quality significantly impacts flavor
- Different brewing methods highlight different characteristics
- Time, temperature, and grind size are the key variables to control
- Freshness of beans dramatically affects quality
### Coffee Preferences
- Light roasts preserve more origin characteristics and acidity
- Dark roasts emphasize body and chocolatey/roasted flavors
- Pour over methods highlight clarity and distinct flavor notes
- Immersion methods create fuller body and rounded flavor
- Personal preference matters more than "correctness"
## Using This Knowledge Base
### For Learning
Use this knowledge base to:
- Understand coffee fundamentals
- Explore connections between brewing methods and flavor outcomes
- Learn how different origins produce distinct flavor profiles
- Discover how equipment affects the brewing process
- Develop a vocabulary for describing coffee experiences
### As a Demo
This knowledge base demonstrates:
- Semantic knowledge organization with categories and relations
- Building connections between related concepts
- Creating a navigable knowledge graph
- Structuring information in a way both humans and AI assistants can understand
- How Basic Memory enables persistent knowledge across conversations
## Relations
- contains [[Coffee Brewing Methods]]
- contains [[Coffee Bean Origins]]
- contains [[Brewing Equipment]]
- contains [[Flavor Extraction]]
- contains [[Tasting Notes]]
- demonstrates [[Basic Memory Capabilities]]
@@ -0,0 +1,79 @@
---
title: Flavor Extraction
type: note
permalink: coffee/flavor-extraction
tags:
- '#coffee'
- '#extraction'
- '#brewing'
- '#science'
- '#demo'
---
# Flavor Extraction
Understanding the science of coffee extraction, how different compounds dissolve at different rates, and how to control extraction to achieve desired flavor profiles.
## Overview
Coffee extraction is the process of dissolving flavor compounds from ground coffee into water. The science of extraction is key to producing a balanced, flavorful cup. Extraction is affected by numerous variables including grind size, water temperature, contact time, agitation, and pressure.
## Observations
- [science] Coffee contains over 1,000 aroma compounds and hundreds of flavor compounds #chemistry
- [principle] Extraction occurs in a predictable sequence: acids → sugars → bitter compounds #extraction_order
- [principle] Under-extraction results in sour, bright, thin coffee lacking sweetness and body #under_extraction
- [principle] Over-extraction results in bitter, hollow, astringent flavors #over_extraction
- [principle] The goal is typically balanced extraction (18-22% of coffee solubles dissolved) #balanced_extraction
- [technique] Finer grind size increases extraction rate due to greater surface area #grind_size
- [technique] Higher water temperature increases extraction rate and solubility of compounds #temperature
- [technique] Longer contact time allows more complete extraction #brew_time
- [technique] Agitation (stirring, turbulence) increases extraction rate by preventing saturation zones #agitation
- [technique] Pressure (as in espresso) can extract compounds that aren't water-soluble at atmospheric pressure #pressure
## Factors Affecting Extraction
- [factor] Grind size: Finer = faster extraction, coarser = slower extraction #grind
- [factor] Water temperature: Higher = faster extraction, lower = slower extraction #temperature
- [factor] Contact time: Longer = more extraction, shorter = less extraction #time
- [factor] Agitation: More = faster extraction, less = slower extraction #agitation
- [factor] Coffee-to-water ratio: More coffee = lower extraction percentage #ratio
- [factor] Water quality: Mineral content affects extraction of different compounds #water
- [factor] Roast level: Darker roasts extract more easily than lighter roasts #roast
- [factor] Bean density: Denser beans (typically high-altitude) require more effort to extract #density
- [factor] Freshness: Freshly roasted coffee extracts differently than aged coffee #freshness
- [factor] Brewing method: Different methods extract different compounds at different rates #method
## Signs of Extraction Levels
- [under] Sour, bright, lack of sweetness, thin body, quick finish #flavor
- [under] Typically from: too coarse grind, too cool water, too short brew time #causes
- [balanced] Sweet, bright but not sour, rich but not bitter, pleasing finish #flavor
- [balanced] Achieved through proper ratio of variables for given coffee #technique
- [over] Bitter, hollow, astringent, dry finish, sometimes papery #flavor
- [over] Typically from: too fine grind, too hot water, too long brew time #causes
## Measuring Extraction
- [method] Total Dissolved Solids (TDS) meters measure concentration of coffee solution #measurement
- [method] Extraction yield = percentage of coffee grounds dissolved in the final brew #calculation
- [preference] Specialty coffee typically targets 18-22% extraction yield #standards
- [preference] Some specialty light roasts may taste best at higher extraction percentages #speciality
## Controlling Extraction
- [technique] Adjust grind size as primary extraction control #basics
- [technique] Use water temperature to fine-tune extraction #fine_tuning
- [technique] Modify pour technique to control agitation level #technique
- [technique] Adjust coffee-to-water ratio to balance strength and extraction #ratio
- [technique] Pre-infusion (blooming) helps achieve even extraction #blooming
- [technique] Pulse pouring creates different extraction dynamics than continuous pour #pour_technique
## Relations
- affected_by [[Coffee Brewing Methods]]
- influenced_by [[Coffee Bean Origins]]
- enhanced_by [[Brewing Equipment]]
- determines [[Tasting Notes]]
- requires [[Water Quality]]
- part_of [[Coffee Knowledge Base]]
@@ -0,0 +1,161 @@
{
"nodes":[
{
"id":"node-5",
"type":"text",
"text":"## Main Pour Phase\n- Use concentric circles from center outward\n- Maintain steady, controlled flow rate\n- Avoid pouring directly on filter walls\n- Keep water level consistent\n- Pulse pour in 2-3 stages (or continuous pour)\n- Total brew time target: 2:30-3:30",
"position":{"x":450,"y":200},
"x":530,
"y":-100,
"width":300,
"height":200,
"color":"1"
},
{
"id":"node-8",
"type":"text",
"text":"## Drawdown\n- Allow water to fully drain\n- Flat bed indicates even extraction\n- Total brew time should be ~2:30-3:30\n- Remove filter promptly after brewing",
"position":{"x":450,"y":700},
"x":540,
"y":375,
"width":300,
"height":150,
"color":"1"
},
{
"id":"node-6",
"type":"text",
"text":"## Pour Pattern\n\nConcentric circles ensure even saturation of coffee grounds. Begin at the center and work outward, avoiding filter edges. Pour height of 1-2 inches above coffee bed.",
"position":{"x":250,"y":450},
"x":960,
"y":25,
"width":300,
"height":150,
"color":"5"
},
{
"id":"node-12",
"type":"text",
"text":"## Tasting Notes\n\n- Balanced extraction: sweet, bright, complex\n- Under-extraction: sour, lacking sweetness\n- Over-extraction: bitter, astringent, hollow\n\nTake notes on each brew to track improvements and preferences.",
"position":{"x":-250,"y":700},
"x":1020,
"y":420,
"width":300,
"height":150,
"color":"6"
},
{
"id":"node-9",
"type":"text",
"text":"## Troubleshooting\n\n- Too sour/weak: Grind finer, water hotter, increase brew time\n- Too bitter/strong: Grind coarser, water cooler, decrease brew time\n- Uneven extraction: Improve pour technique, better grinder\n- Channeling: More careful pouring, better bloom\n- Slow drawdown: Coarser grind, less agitation\n- Fast drawdown: Finer grind, more careful pouring",
"position":{"x":100,"y":700},
"x":30,
"y":570,
"width":300,
"height":200,
"color":"6"
},
{
"id":"node-3",
"type":"text",
"text":"## Preparation\n- Heat water to 195-205°F (90-96°C)\n- Measure coffee (1:15 to 1:17 ratio)\n- Medium-fine grind (sea salt consistency)\n- Rinse filter with hot water\n- Discard rinse water\n- Add ground coffee to filter\n- Level coffee bed",
"position":{"x":-250,"y":200},
"x":30,
"y":-500,
"width":300,
"height":200,
"color":"3"
},
{
"id":"node-1",
"type":"text",
"text":"# Perfect Pour Over Method\n\nA systematic approach to brewing exceptional pour over coffee by controlling key variables and following proper technique.",
"position":{"x":0,"y":0},
"x":-580,
"y":-760,
"width":400,
"height":120,
"color":"4"
},
{
"id":"node-10",
"type":"text",
"text":"## Grinding Parameters\n\n- V60: Medium-fine (sea salt)\n- Chemex: Medium (slightly coarser than V60)\n- Kalita Wave: Medium (between V60 and Chemex)\n\nConsistent particle size is critical; use quality burr grinder.",
"position":{"x":-250,"y":450},
"x":30,
"y":-910,
"width":300,
"height":150,
"color":"5"
},
{
"id":"node-2",
"type":"text",
"text":"## Equipment Setup\n- Clean V60/Chemex/Kalita Wave\n- Paper filter (rinsed)\n- Server/mug\n- Scale with timer\n- Gooseneck kettle\n- Burr grinder\n- Fresh coffee beans",
"position":{"x":-600,"y":200},
"x":-530,
"y":-500,
"width":300,
"height":200,
"color":"3"
},
{
"id":"node-4",
"type":"text",
"text":"## The Bloom\n- Start timer\n- Pour 2-3x coffee weight water\n- Ensure all grounds are saturated\n- Gentle stir or swirl if needed\n- Allow 30-45 seconds for degassing\n- Look for bubbling and dome formation",
"position":{"x":100,"y":200},
"x":530,
"y":-500,
"width":300,
"height":200,
"color":"1"
},
{
"id":"node-13",
"type":"text",
"text":"## Coffee-to-Water Ratio\n\n- Standard: 1:15 to 1:17 (coffee:water)\n- Stronger cup: 1:15 (67g/L)\n- Medium cup: 1:16 (62.5g/L)\n- Lighter cup: 1:17 (58.8g/L)\n\nExample: For 300ml water, use ~18-20g coffee",
"position":{"x":-600,"y":700},
"x":30,
"y":-100,
"width":300,
"height":150,
"color":"6"
},
{
"id":"node-7",
"type":"text",
"text":"## Brew Time Guideline\n\n- Bloom: 30-45 seconds\n- First pour: 1:00-1:15\n- Second pour: 1:45-2:00\n- Final pour: 2:15-2:30\n- Drawdown complete: 2:45-3:30\n\nAdjust for taste: shorter for lighter, longer for stronger",
"position":{"x":600,"y":450},
"x":-80,
"y":220,
"width":300,
"height":200,
"color":"5"
},
{
"id":"node-11",
"type":"text",
"text":"## Water Quality\n\n- Clean, filtered water\n- No strong odors or flavors\n- Ideal TDS: 75-150 ppm\n- Ideal pH: 7.0-7.5\n- Avoid distilled water (lacks minerals)\n- Avoid hard water (scaling issues)",
"position":{"x":-600,"y":450},
"x":-780,
"y":-125,
"width":300,
"height":150,
"color":"5"
}
],
"edges":[
{"id":"edge-1","fromNode":"node-1","fromSide":"bottom","toNode":"node-2","toSide":"top","label":"Step 1"},
{"id":"edge-2","fromNode":"node-2","fromSide":"right","toNode":"node-3","toSide":"left","label":"Step 2"},
{"id":"edge-3","fromNode":"node-3","fromSide":"right","toNode":"node-4","toSide":"left","label":"Step 3"},
{"id":"edge-4","fromNode":"node-4","fromSide":"bottom","toNode":"node-5","toSide":"top","label":"Step 4"},
{"id":"edge-5","fromNode":"node-5","fromSide":"bottom","toNode":"node-8","toSide":"top","label":"Step 5"},
{"id":"edge-6","fromNode":"node-5","fromSide":"left","toNode":"node-7","toSide":"right","label":"Timing"},
{"id":"edge-7","fromNode":"node-5","fromSide":"right","toNode":"node-6","toSide":"left","label":"Technique"},
{"id":"edge-8","fromNode":"node-8","fromSide":"left","toNode":"node-9","toSide":"right","label":"if problems"},
{"id":"edge-9","fromNode":"node-3","fromSide":"top","toNode":"node-10","toSide":"bottom","label":"Grinding details"},
{"id":"edge-10","fromNode":"node-2","fromSide":"bottom","toNode":"node-11","toSide":"right","label":"Water details"},
{"id":"edge-11","fromNode":"node-8","fromSide":"right","toNode":"node-12","toSide":"left","label":"Evaluate"},
{"id":"edge-12","fromNode":"node-3","fromSide":"bottom","toNode":"node-13","toSide":"top","label":"Ratio details"}
]
}
+84
View File
@@ -0,0 +1,84 @@
---
title: Tasting Notes
type: note
permalink: coffee/tasting-notes
tags:
- '#coffee'
- '#tasting'
- '#flavor'
- '#cupping'
- '#demo'
---
# Tasting Notes
How to taste and evaluate coffee, identify flavor characteristics, and develop a personal coffee palate.
## Overview
Coffee tasting, or "cupping" in professional contexts, is the practice of observing the tastes and aromas of brewed coffee. Developing a coffee palate helps identify preferences, communicate about coffee experiences, and better understand how brewing variables affect the cup.
## Observations
- [principle] Flavor perception includes taste, aroma, mouthfeel, and retronasal perception #sensory
- [principle] Our taste buds can only perceive sweet, sour, salty, bitter, and umami #taste
- [principle] Most of what we call "flavor" is actually aroma detected retronasally #aroma
- [technique] Professional coffee tasting (cupping) uses a standardized protocol for consistency #cupping
- [technique] Slurping coffee aerates it and spreads it across all taste receptors #technique
- [technique] Allowing coffee to cool reveals different flavor notes at different temperatures #temperature
## Coffee Flavor Wheel
- [tool] The SCA Coffee Flavor Wheel provides a standardized vocabulary for describing coffee #flavor_wheel
- [category] Primary categories include: Fruity, Floral, Sweet, Nutty/Cocoa, Spice, Roasted, Other #categories
- [subcategory] Fruity breaks down into: Berry, Dried Fruit, Citrus Fruit, Stone Fruit, Tropical Fruit, etc. #fruit_notes
- [subcategory] Floral includes: Floral, Black Tea, Chamomile, Rose, Jasmine, etc. #floral_notes
- [subcategory] Sweet includes: Brown Sugar, Molasses, Honey, Maple Syrup, Vanilla, etc. #sweet_notes
- [subcategory] Nutty/Cocoa includes: Nut, Cocoa, Dark Chocolate, Chocolate, etc. #nutty_notes
- [subcategory] Spice includes: Brown Spice, Pepper, Anise, Nutmeg, Cinnamon, etc. #spice_notes
## Basic Tasting Components
- [component] Acidity: The bright, tangy quality (not sourness from under-extraction) #acidity
- [component] Sweetness: The pleasant, sugary quality balancing other elements #sweetness
- [component] Body: The physical mouthfeel and weight of the coffee #body
- [component] Finish/Aftertaste: The flavor that lingers after swallowing #finish
- [component] Balance: How well all elements work together #balance
- [component] Complexity: The range and layers of distinct flavors #complexity
- [component] Cleanliness: Absence of defects or off-flavors #cleanliness
## Common Flavor Notes by Origin
- [ethiopia] Blueberry, jasmine, bergamot, lemon, tea-like #flavor_notes
- [kenya] Blackcurrant, grapefruit, tomato-like acidity, winey #flavor_notes
- [colombia] Caramel, red apple, nuts, chocolate, balanced acidity #flavor_notes
- [guatemala] Chocolate, spice, apple, medium acidity #flavor_notes
- [brazil] Nuts, chocolate, low-to-medium acidity, full body #flavor_notes
- [indonesia] Earthy, herbal, spice, cedar, full body, low acidity #flavor_notes
- [costa_rica] Clean, bright, citrus, balanced, light chocolate #flavor_notes
## Developing Your Palate
- [technique] Taste coffees side-by-side to identify differences #comparison
- [technique] Try describing flavors before looking at roaster's notes #blind_tasting
- [technique] Keep a coffee journal with detailed notes about each coffee #journaling
- [technique] Explore different processing methods of the same origin #processing
- [technique] Try the same coffee brewed with different methods #brewing_comparison
- [technique] Use reference flavors (actual fruits, chocolates, etc.) to calibrate your palate #calibration
## Personal Coffee Experiences
- [experience] Ethiopian Yirgacheffe prepared as pour over: intense blueberry, jasmine aromatics, tea-like body
- [experience] Sumatra Mandheling in French press: earthy, cedar, herbal, tobacco, full body
- [experience] Panama Gesha as pour over: intense floral notes, jasmine, bergamot, delicate body
- [experience] Brazil Cerrado as espresso: nutty, chocolate, caramel, low acidity, great crema
- [experience] Kenya AA as pour over: bright blackcurrant, tomato-like acidity, winey finish
## Relations
- determined_by [[Flavor Extraction]]
- influenced_by [[Coffee Bean Origins]]
- varies_with [[Coffee Brewing Methods]]
- enhanced_by [[Proper Grinding Technique]]
- documented_in [[Coffee Journal]]
- part_of [[Coffee Knowledge Base]]
View File
@@ -20,7 +20,7 @@ def ai_assistant_guide() -> str:
A focused guide on Basic Memory usage.
"""
logger.info("Loading AI assistant guide resource")
guide_doc = Path(__file__).parent.parent.parent.parent.parent / "data/ai_assistant_guide.md"
guide_doc = Path(__file__).parent.parent.parent.parent.parent / "static" /" ai_assistant_guide.md"
content = guide_doc.read_text()
logger.info(f"Loaded AI assistant guide ({len(content)} chars)")
return content