What are the required dependencies?
You need `mcp`, `langchain`, `langchain‑openai`, `langgraph`, and `python‑dotenv` installed via pip or pipenv.
MCP to LangChain/LangGraph Adapter
@SDCalvo
Basic information
About MCP to LangChain/LangGraph Adapter
Addapter that turns MCP server tools into langchain usable tools
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.
RepositoryMCP to LangChain/LangGraph Adapter 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 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
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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