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

git clone <your-repo-url>
cd Learn_MCP

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.