This server gives Claude semantic search across the entire LangChain ecosystem through four tools: search_docs for documentation and tutorials, plus search_langchain_code, search_langgraph_code, and search_deepagents_code for finding implementation examples in Python and JavaScript repositories. It's powered by ChromaDB and OpenRouter embeddings, requiring Google OAuth to access the hosted API with usage credits. Reach for this when you're building with LangChain and need to quickly surface relevant code patterns or API references without context switching to docs. The project also includes self-hosting instructions if you want to run your own embedding pipeline locally, ingesting from the official repos and serving through your own API endpoint.
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.
# 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
Add the following configuration to your client's config file:
Claude Desktop
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonCursor
~/.cursor/mcp.json%USERPROFILE%\.cursor\mcp.json{
"mcpServers": {
"langchain-mcp": {
"command": "npx",
"args": ["langchain-mcp"]
}
}
}
langchain-mcp login # Login via Google OAuth
langchain-mcp status # Check usage and remaining credits
langchain-mcp logout # Logout and clear credentials
| 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 |
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
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
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"]
}
]
}
sentence-transformer (local)openaicoheregoogleollamaopenrouter (default)See ChromaDB Integrations for more options.
The project includes automated deployment scripts for VPS hosting:
# Manual deployment
./deploy.sh
# GitHub Actions (production branch)
git push origin main:production
Deployment includes:
Forking and contributions are welcome!
MIT License - see the LICENSE file for details.
Built with ❤️ by baixianger
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