Community MCP server providing LangChain capabilities. Agents can build and execute LangChain chains, manage vector stores for RAG (retrieval-augmented generation), use LangChain's document loaders and text splitters, and orchestrate multi-step agent workflows. Bridges MCP and LangChain ecosystems. Useful for building sophisticated RAG pipelines and multi-step reasoning agents.
pip install langchain-mcp-adapters
{
"mcpServers": {
"langchain": {
"args": [
"-m",
"langchain_mcp_adapters"
],
"command": "python"
}
}
}List available chains
{
"type": "object",
"required": [],
"properties": {}
}// Input
{}// Output
{
"chains": [
{
"id": "summarize",
"name": "Text Summarizer"
},
{
"id": "qa",
"name": "Q&A Chain"
}
]
}Execute LangChain chain
{
"type": "object",
"required": [
"chain_id",
"input"
],
"properties": {
"input": {
"type": "object"
},
"chain_id": {
"type": "string"
}
}
}// Input
{
"input": {
"text": "Long article..."
},
"chain_id": "summarize"
}// Output
{
"output": "Summary: The article discusses...",
"tokens_used": 250
}Community MCP server providing LangChain capabilities. Agents can build and execute LangChain chains, manage vector stores for RAG (retrieval-augmented generation), use LangChain's document loaders and text splitters, and orchestrate multi-step agent workflows. Bridges MCP and LangChain ecosystems. Useful for building sophisticated RAG pipelines and multi-step reasoning agents.
LangChain provides 2 tools including list_chains, run_chain.
Yes, LangChain is completely free to use with no usage limits on the free tier.
You can install LangChain using the following command: pip install langchain-mcp-adapters. After installation, add the provided config snippet to your Claude Desktop or Cursor configuration.
LangChain is listed under the AI & Machine Learning category in the AgentForge MCP registry.
LangChain has a current uptime of 99.78% with an average response time of 380ms.
To connect LangChain, click the "Connect Agent" button on this page to get the configuration snippet. Add it to your MCP client (Claude Desktop, Cursor, or any MCP-compatible tool). Your AI agent will then have access to all of LangChain's tools via the Model Context Protocol.