Skip to main content

Model context protocol connector for LangChain

Project description

Langchain Model Context Protocol Connector

build status GitHub Release

Introduction

This project introduces tools to easily integrate Anthropic Model Context Protocol(MCP) with langchain. It provides a simple way to connect to MCP servers and access tools that can be made available to LangChain.

MCP integrations with langchain expands the capabilities of LLM by providing access to an ecosystem of community build servers and additional resources. This means that we do not need to create custom tools for each LLM, but rather use the same tools across different LLMs.

Installation

pip install langchain-mcp-connect

What is the Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is an open-source standard released by Anthropic. The Model Context Protocol highlights the importance of tooling standardisation through open protocols. Specifically, it standardises how applications interact and provide context to LLMs. Just like how HTTP standardises how we communicate across the internet, MCP provides a standard protocol for LLM to interact with external tools. You can find out more about the MCP at https://github.com/modelcontextprotocol and https://modelcontextprotocol.io/introduction.

Example usage

The langchain_mcp_connect contain key methods to determine available tools in the model context protocol. Before starting, please ensure you meet the pre-requisites. For a detail example on how langchain_mcp_connect can be used, see this demo project.

Pre requisites

  1. Install uv

Defining a tool

Define your tool within claude_mcp_config.json file in the root directory. For a list of available tools and how to configure tools see here.

{
  "mcpServers": {
    "git": {
      "command": "uvx",
      "args": ["mcp-server-git", "--repository", "./"]
    },
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "./"
      ]
    },
    "github": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-github"
      ],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ENV_GITHUB_PERSONAL_ACCESS_TOKEN"
      }
    }
  }
}

Environment Variables

Managing secrets is a key aspect of any project. The langchain_mcp_connect tool is able to inject secrets from the current environment. To do so, prefix the name of your environment variable with ENV_ in claude_mcp_config.json to inject environment variables into the current context. In the example above, ensure you have defined GITHUB_PERSONAL_ACCESS_TOKEN in your current environment with:

export GITHUB_PERSONAL_ACCESS_TOKEN="<YOUR_TOKEN_HERE>"
export OPENAI_API_KEY="<YOUR_KEY_HERE>"

Running the example

uv run src/example/agent.py

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

langchain_mcp_connect-2.0.3.tar.gz (32.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

langchain_mcp_connect-2.0.3-py3-none-any.whl (7.0 kB view details)

Uploaded Python 3

File details

Details for the file langchain_mcp_connect-2.0.3.tar.gz.

File metadata

File hashes

Hashes for langchain_mcp_connect-2.0.3.tar.gz
Algorithm Hash digest
SHA256 d94e2fb1d04366946443d82912813be974aec87e7817fd7ac2f84c5e57b172f7
MD5 f12b3ded53a5bfadc1f09203d18ea685
BLAKE2b-256 9f9092dcf2d05b590c7fa6025cfe5ff16851e0c0579f26d8c209a5af8c42b295

See more details on using hashes here.

File details

Details for the file langchain_mcp_connect-2.0.3-py3-none-any.whl.

File metadata

File hashes

Hashes for langchain_mcp_connect-2.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 124e44842729e47d6caaaa87170b14b59504a5ebeb2e6d377c7c52a2b089fa84
MD5 f5c496bd00dc701fc74d0c0c636d3c63
BLAKE2b-256 0fbd015302187846eb0a61f608f75320e2d1685d0ce9083997be4bf82ac05041

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page