Learn_MCP Math Server

# 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](https://github.com/astral-sh/uv) (a fast Python package manager) - A valid GROQ API key (for ChatGroq) ## 1. Clone the Repository ``` git clone <your-repo-url> cd mathServer-FastMCP ``` ## 2. Create and Activate a Virtual Environment (optional but recommended) ``` python -m venv .venv # On Windows: .venv\Scripts\activate # On macOS/Linux: source .venv/bin/activate ``` ## 3. Install Dependencies with uv ``` uv pip install -r requirements.txt ``` Or, to use the lockfile (if present): ``` uv pip sync uv.lock ``` ## 4. Set Up Environment Variables Create a `.env` file in the project root with your GROQ API key: ``` GROQ_API_KEY=your_groq_api_key_here ``` ## 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 ``` uv pip run python client.py ``` Or simply: ``` python client.py ``` ## 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 valid `GROQ_API_KEY`. ## 8. Project Structure - `client.py` — Main client that connects to the math MCP server - `mathserver.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.