MCP + LangGraph Agent

@hirokiyn

Repository

Basic information

About MCP + LangGraph Agent

LangGraph agent tutorial adapted to use MCP servers.

#agent #mcp #langchain #langgraph

MCP + LangGraph Agent config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

MCP + LangGraph Agent tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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.

Frequently asked questions

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.

Comments

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