MCP Servers

LangChain Anthropic MCP Server

Exposes LangChain and Anthropic Claude capabilities as tools for generating production-ready RAG systems, Supabase vector stores, and document ingestion pipelines. It enables users to instantly scaffold AI infrastructure and document processing code through natural language prompts in MCP-compatible clients.

README

LangChain Anthropic MCP Server

🚀 MCP server that exposes LangChain + Anthropic Claude capabilities as tools - instantly generate production-ready RAG systems, Supabase vector stores, document ingestion pipelines, and more!

Perfect for use with Cursor AI or any MCP client.

🚀 Quick Start

Installation for Cursor

Add to your Cursor mcp.json:

{
  "mcpServers": {
    "langchain-anthropic": {
      "command": "npx",
      "args": [
        "-y",
        "spencer-life/langchain-anthropic-mcp-server"
      ],
      "env": {}
    }
  }
}

That's it! Restart Cursor and start using it.

💡 Usage

Once installed, ask your AI assistant:

"Use langchain-anthropic to setup a Supabase vector store"
"Use langchain-anthropic to create a RAG chain with Claude Sonnet"
"Use langchain-anthropic to generate PDF document ingestion code"

The AI will call the appropriate tool and return complete, production-ready code!

🛠️ Available Tools

✅ setup_supabase_vectorstore - Complete Supabase vector store setup
✅ create_rag_chain - Full RAG with Claude
✅ generate_document_ingestion - Document loading & chunking
✅ create_conversational_rag - RAG with conversation memory
✅ setup_hybrid_search - Vector + keyword search
✅ create_multi_query_retriever - Multi-query for better recall
✅ setup_extended_thinking - Extended thinking configuration
✅ generate_package_setup - Complete dependencies

📝 License

MIT License

Built with ❤️ for the LangChain and MCP community

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