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
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.txtand install any missing dependencies. - Make sure your
.envfile 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.