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MCP + LangGraph Agent

@hirokiyn

リポジトリ

MCP + LangGraph Agent について

LangGraph agent tutorial adapted to use MCP servers.

#agent#mcp#langchain#langgraph

基本情報

カテゴリ

推論

ランタイム

python

トランスポート

stdio

公開者

hirokiyn

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

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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 + LangGraph Agent?

It is a minimal, functional example of an agent powered by LangGraph where tools are implemented using MCP (Model Context Protocol) servers instead of traditional LangChain tools. It is based on the official LangGraph tutorial and is intended as a skeleton for building custom LangGraph agents with MCP tools.

How to use MCP + LangGraph Agent?

Clone the repository, install dependencies using Poetry, and set the Anthropic API key in the .env file. Start the MCP servers (python src/mcp_servers/math_server.py and python src/mcp_servers/weather_server.py), then run poetry run main to launch the agent in interactive mode.

Key features of MCP + LangGraph Agent

  • Integrates LangGraph for managing agent state and message routing.
  • Uses MCP servers to provide access to tools.
  • Includes example MCP servers for math and weather.
  • Provides a command-line interface for interacting with the agent.

Use cases of MCP + LangGraph Agent

  • Building a custom LangGraph agent with MCP-based tools.
  • Experimenting with MCP integration in a LangGraph workflow.
  • Prototyping an interactive CLI agent with math and weather capabilities.
  • Using the project as a skeleton for rapid agent development.

FAQ from MCP + LangGraph Agent

What does this project demonstrate?

It demonstrates how to integrate MCP servers as tools in a LangGraph agent, using math and weather as example servers.

How do I install and run the agent?

Clone the repository, install dependencies with Poetry, set your Anthropic API key in .env, start the MCP servers, and run poetry run main for interactive mode.

Can I change the LLM used by the agent?

Yes, the LLM configuration can be changed in src/common.py.

How do I configure which MCP servers are used?

The MCP servers are configured in src/main.py; you can modify the configuration to add or remove servers, or to change the transport mechanism.

What are the example tools included?

The example tools are a math server and a weather server, each providing basic functions like arithmetic and weather data retrieval.

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