Automatically detects git repositories to namespace and isolate memories per-repo, with cross-repo memory support and automatic repository indexing for semantic code search.
Supports repository-based memory management with automatic detection and indexing of GitHub repositories for context-aware semantic search and code navigation.
Provides hosted deployment storage backend using PostgreSQL with pgvector extension for vector embeddings, semantic search, and team sharing of memories.
Distributed as a Python package on PyPI for installation and deployment of the ContextFS memory layer.
Default local storage backend using SQLite with FTS5 for keyword search, memory storage, and session management.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@ContextFS search for recent decisions about database architecture"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Persistent Memory for AI Agents - Give your AI tools memory that persists across sessions.
Full Documentation | Get Started
# With pip
pip install contextfs
# With uv (recommended)
uv pip install contextfs
# Run directly without installing
uvx contextfsRelated MCP server: hive-memory
# 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 indexAdd 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.
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
from contextfs import ContextFS
ctx = ContextFS()
# Save
ctx.save("Use JWT for auth", type="decision", tags=["auth"])
# Search
results = ctx.search("authentication")Enable cross-device memory sync:
contextfs cloud login
contextfs cloud syncSign up at contextfs.ai for cloud features.
Visit contextfs.ai/docs for:
Installation guides for each AI tool
API reference
Memory types and best practices
Cloud sync setup
MIT - Matthew Long and The YonedaAI Collaboration
This server cannot be deployed
Universal memory for AI agents and tools. Save, organize and search context anywhere.
Universal persistent memory and knowledge retrieval layer for AI agents and LLMs.
Persistent memory for AI agents. Semantic search, memory graph, W3C DID identity.
Shared memory for coding agents. Stop re-explaining your codebase every session.
