langchain-mcp

langchain-mcp

Provides semantic search across the entire LangChain ecosystem, including documentation and source code for LangChain, LangGraph, LangSmith, and DeepAgents.

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LangChain MCP

Give your AI assistant complete knowledge of LangChain, LangGraph & LangSmith

Website npm version License: MIT

Website • Installation • Features • Documentation

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Overview

LangChain MCP is a Model Context Protocol (MCP) server that provides semantic search across the entire LangChain ecosystem. Build AI applications faster with instant access to documentation and source code for LangChain, LangGraph, LangSmith, and DeepAgents.

<img src="img/homepage.png" alt="LangChain MCP Homepage" width="800">

Features

  • Semantic Search - Natural language queries across all LangChain ecosystem docs
  • Source Code Search - Find code examples in Python and JavaScript repositories
  • MCP Protocol - Works seamlessly with Claude Code, Claude Desktop, Cursor, and any MCP-compatible client
  • Production Ready - Scalable API with authentication and usage tracking
  • Fast & Accurate - Powered by ChromaDB and OpenRouter embeddings

Installation

Quick Start (Recommended)

# Install globally
npm install -g langchain-mcp

# Login with Google
langchain-mcp login

# Add to Claude Code
claude mcp add langchain-mcp -- npx langchain-mcp

Manual Configuration

Add the following configuration to your client's config file:

Claude Desktop

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Cursor

  • macOS/Linux: ~/.cursor/mcp.json
  • Windows: %USERPROFILE%\.cursor\mcp.json
{
  "mcpServers": {
    "langchain-mcp": {
      "command": "npx",
      "args": ["langchain-mcp"]
    }
  }
}

Usage

CLI Commands

langchain-mcp login      # Login via Google OAuth
langchain-mcp status     # Check usage and remaining credits
langchain-mcp logout     # Logout and clear credentials

Available MCP Tools

Tool Description Parameters
search_docs Search documentation, references, and tutorials query, limit (default: 5)
search_langchain_code Search LangChain source code query, language (py/js), limit
search_langgraph_code Search LangGraph source code query, language (py/js), limit
search_deepagents_code Search DeepAgents source code query, language (py/js), limit

Pricing

  • Free tier available for new users
  • Donation bonus for supporters

Documentation

Self-deploy

Project Structure

langchain-MCP/
├── packages/
│   ├── ingest/              # Python - Data ingestion (uv)
│   ├── api/                 # TypeScript - API server (Express)
│   ├── mcp-server/          # TypeScript - MCP client (npm package)
│   └── mcp-server-local/    # TypeScript - Local MCP server (dev)
├── config/
│   └── settings.json        # Shared configuration
└── deploy.sh                # Deployment script

Architecture

<img src="img/Architecture.png" alt="Architecture" width="600">

Setup Development Environment

1. Ingest Documentation & Source Code

cd packages/ingest
uv sync
uv run ingest --list     # List available repositories
uv run ingest docs       # Ingest documentation only
uv run ingest            # Ingest all (docs + code)

2. Run API Server

cd packages/api
npm install
npm run dev              # Development server on port 3000

3. Test Local MCP Server

cd packages/mcp-server-local
npm install
npm run dev

Configuration

All settings in config/settings.json:

{
  "embedding": {
    "provider": "openrouter",
    "model": "qwen/qwen3-embedding-8b"
  },
  "chromadb": {
    "path": "./data/chroma"
  },
  "chunking": {
    "docs": { "chunk_size": 2000, "chunk_overlap": 200 },
    "code": { "chunk_size": 4000, "chunk_overlap": 200 }
  },
  "repos": [
    {
      "name": "langchain",
      "url": "https://github.com/langchain-ai/langchain",
      "type": "code",
      "languages": ["python", "javascript"]
    }
  ]
}

Supported Embedding Providers

  • sentence-transformer (local)
  • openai
  • cohere
  • google
  • ollama
  • openrouter (default)

See ChromaDB Integrations for more options.

Deployment

The project includes automated deployment scripts for VPS hosting:

# Manual deployment
./deploy.sh

# GitHub Actions (production branch)
git push origin main:production

Deployment includes:

  • Code synchronization via rsync
  • Automatic npm installation and build
  • PM2 process management
  • Nginx static file serving
  • Environment variable management

Roadmap

  • [x] Semantic search across docs and code
  • [x] Google OAuth authentication
  • [x] Usage tracking and credits system
  • [x] MCP registry registration
  • [x] Claude Code, Desktop, and Cursor support
  • [ ] Rate limiting (per user / per IP)
  • [ ] Additional embedding model options
  • [ ] Local mode (no API key required)
  • [ ] Browser extension for quick searches
  • [ ] VSCode extension integration

Contributing

Forking and contributions are welcome!

Support

License

MIT License - see the LICENSE file for details.


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Built with ❤️ by baixianger

Website • GitHub • npm

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