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MCP to LangChain/LangGraph Adapter

@SDCalvo

リポジトリ

基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

SDCalvo

MCP to LangChain/LangGraph Adapter について

Addapter that turns MCP server tools into langchain usable tools

#mcp#langchain#adapter

MCP to LangChain/LangGraph Adapter の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

MCP to LangChain/LangGraph Adapter のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP to LangChain/LangGraph Adapter?

It bridges MCP (Multi‑modal Conversational Procedure) servers and LangChain/LangGraph frameworks, converting MCP tools into LangChain‑compatible tools for use in agents, chains, and graph‑based AI applications.

How to use MCP to LangChain/LangGraph Adapter?

Install the required Python packages (mcp, langchain, langchain‑openai, langgraph, python‑dotenv). Create an MCP server script (e.g., simple_server.py), then instantiate MCPAdapter with the script path. Call get_tools() to retrieve LangChain tools and integrate them into LangChain agents or LangGraph react agents.

Key features of MCP to LangChain/LangGraph Adapter

  • Connects to any MCP server via stdio transport.
  • Automatically discovers and converts MCP tools to LangChain BaseTool.
  • Supports both LangChain agents and LangGraph react agents.
  • Manages conversation history with LangGraph memory checkpoints.
  • Allows custom environment variables per server process.

Use cases of MCP to LangChain/LangGraph Adapter

  • Adding MCP‑exposed tools (e.g., math, weather) to an LLM agent.
  • Building conversational agents in LangGraph with persistent state.
  • Wrapping legacy or custom tools as MCP servers for LangChain pipelines.

よくある質問

1

What are the required dependencies?

You need `mcp`, `langchain`, `langchain‑openai`, `langgraph`, and `python‑dotenv` installed via pip or pipenv.

2

How do I connect to an MCP server?

Provide the path to the MCP server script to `MCPAdapter`; the adapter launches and manages the server process automatically over stdio.

3

Do I need an API key?

The adapter itself requires no API key. To use OpenAI models in examples, set an `OPENAI_API_KEY` in a `.env` file or environment.

4

What transport does the adapter use?

The provided examples use stdio transport. Other transports are not documented in the README.

5

How can I debug connection issues?

Add logging to your MCP server script with `logging.basicConfig` to capture debug output to a file and stream.

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