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MCP to LangChain/LangGraph Adapter

@SDCalvo

MCP to LangChain/LangGraph Adapter について

Addapter that turns MCP server tools into langchain usable tools

基本情報

カテゴリ

AI とエージェント

ランタイム

python

トランスポート

stdio

公開者

SDCalvo

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

ツール

ツールは検出されませんでした

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.

FAQ from MCP to LangChain/LangGraph Adapter

What are the required dependencies?

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

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.

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.

What transport does the adapter use?

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

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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