MCP to LangChain/LangGraph Adapter

@SDCalvo

Repository

Basic information

About MCP to LangChain/LangGraph Adapter

Addapter that turns MCP server tools into langchain usable tools

#mcp #langchain #adapter

MCP to LangChain/LangGraph Adapter 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 to LangChain/LangGraph Adapter tools

Tool list not available yet

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

Overview

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.

Frequently asked questions

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.

Comments

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