Manages environment variables for the MCP server, specifically handling API key storage for external services like GROQ
Used for implementing the MCP server interface through the langchain_mcp_adapters.fastapi module
Enables integration with LangChain, allowing the math server to be used as a tool within LangChain workflows for mathematical operations
Learn_MCP Project Setup Guide
This guide will help you set up and run the Learn_MCP project, which demonstrates using a Model Context Protocol (MCP) math server with LangChain.
Prerequisites
- Python 3.8 or higher (recommended: use a virtual environment)
- uv (a fast Python package manager)
- A valid GROQ API key (for ChatGroq)
1. Clone the Repository
2. Create and Activate a Virtual Environment (optional but recommended)
3. Install Dependencies with uv
Or, to use the lockfile (if present):
4. Set Up Environment Variables
Create a .env
file in the project root with your GROQ API key:
5. Run the Math Server
The math server will be started automatically by the client script as a subprocess (mathserver.py
). You do not need to start it manually.
6. Run the Client
Or simply:
7. Troubleshooting
- If you see
ImportError: langchain_mcp_adapters.fastapi could not be resolved
, ensure the package is installed or available in your environment. - If you get errors about missing modules, check your
requirements.txt
and install any missing dependencies. - Make sure your
.env
file is present and contains a validGROQ_API_KEY
.
8. Project Structure
client.py
— Main client that connects to the math MCP servermathserver.py
— Math MCP server (started by the client)requirements.txt
— Python dependencies.env
— Environment variables (not committed to version control)
Feel free to update this README with additional details as your project evolves.
This server cannot be installed
A Model Context Protocol (MCP) server that demonstrates mathematical capabilities through a LangChain integration, allowing clients to perform math operations via the MCP protocol.
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