ContextFS
Persistent Memory for AI Agents - Give your AI tools memory that persists across sessions.
Full Documentation | Get Started
Install
# With pip
pip install contextfs
# With uv (recommended)
uv pip install contextfs
# Run directly without installing
uvx contextfs
Quick Start
# Initialize your repo for indexing
contextfs index init
# Save a memory
contextfs memory save "Use PostgreSQL for database" --type decision
# Search memories
contextfs memory search "database"
# Index your codebase for semantic search
contextfs index index
MCP Integration
Add to your AI tool's MCP config:
{
"mcpServers": {
"contextfs": {
"command": "uvx",
"args": ["contextfs"]
}
}
}
Works with: Claude Code, Claude Desktop, Cursor, VS Code, and any MCP-compatible client.
See tool-specific setup guides for detailed instructions.
Key Features
- Semantic Search - Find relevant memories using natural language
- Auto Code Indexing - Index your entire codebase for context-aware AI
- Cross-Session Memory - Decisions, facts, and patterns persist across conversations
- Multi-Tool Sync - Share memory between Claude, Cursor, VS Code, and more
Python SDK
from contextfs import ContextFS
ctx = ContextFS()
# Save
ctx.save("Use JWT for auth", type="decision", tags=["auth"])
# Search
results = ctx.search("authentication")
Cloud Sync
Enable cross-device memory sync:
contextfs cloud login
contextfs cloud sync
Sign up at contextfs.ai for cloud features.
Documentation
Visit contextfs.ai/docs for:
- Installation guides for each AI tool
- API reference
- Memory types and best practices
- Cloud sync setup
License
MIT - Matthew Long and The YonedaAI Collaboration
