Is this the official LangChain MCP integration?
No. LangChain now has a more official implementation called `langchain-mcp-adapters`. This repository is a community alternative.
@rectalogic
Basic information
Model Context Protocol tool support for LangChain
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"langchain-mcp": {
"command": "uv",
"args": [
"run",
"tests/demo.py",
"Read and summarize the file ./LICENSE"
]
}
}
}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.
langchain-mcp provides Model Context Protocol (MCP) tool calling support within LangChain. It enables LangChain applications to use tools exposed by any MCP server by wrapping them as LangChain BaseTool instances. This is for developers building LangChain-based agents or chains that need to call external tools via the MCP standard.
Create a langchain_mcp.MCPToolkit by passing it an mcp.ClientSession, then call await toolkit.initialize() followed by toolkit.get_tools() to retrieve a list of LangChain BaseTools. The toolkit handles the MCP client‑server lifecycle and tool discovery.
MCPToolkit class for session managementBaseTool objectsClientSessionNo. LangChain now has a more official implementation called `langchain-mcp-adapters`. This repository is a community alternative.
It requires Python and can be installed via PyPI as `langchain-mcp`. The demo also uses the `uv` tool for running.
Set the `GROQ_API_KEY` environment variable and execute `uv run tests/demo.py "Read and summarize the file ./LICENSE"` (or equivalent) against an MCP filesystem server.
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