Modelcontextprotocolserver

🚀 MCP Server – Overview

The Model Context Protocol (MCP) Server is a lightweight, flexible bridge between large language models (like Claude or ChatGPT) and real-world applications or system operations. It allows AI models to perform tasks such as running terminal commands, accessing camera devices, or retrieving weather data — all through structured tool-calling interfaces.

By separating logic and execution layers, the MCP server ensures a safe and controllable way for models to interact with your machine, providing modularity, transparency, and extensibility.

⚙️ Installation Guide

This project uses uv to manage the Python environment and dependencies.

1. Install uv

MacOS:

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows (PowerShell):

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

2. Navigate to Your Project Folder

cd Project_Folder

3. Initialize the Project with uv

uv init

4. Add MCP as a Dependency

uv add "mcp[cli]"

🚧 Running Any MCP Server

Before running any MCP server file, you must activate the virtual environment:

MacOS/Linux:

source venv/bin/activate

Windows:

venv\Scripts\activate

Then install and run the desired MCP module:

mcp install Python-Filename.py

Replace Python-Filename.py with the actual MCP file you want to run (e.g., terminal.py, camera.py, weather.py).

⚠️ Troubleshooting

If any MCP server does not work as expected, you may need to modify the config file used by the MCP server.

Open the claude_desktop_config.json (for claude) or the relevant configuration file and change

{
  "mcpServers": {
    "Name of the mcp server": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "Path to the mcp file"
      ]
    }
  }
}

to:

{
  "mcpServers": {
    "Name of the mcp server": {
      "command": "mcp",
      "args": [
        "run",
        "Path to the mcp file"
      ]
    }
  }
}