mcp-my-mac

MCP My Mac

A lightweight server that exposes Mac system information via a simple API, allowing AI assistants like Claude to access real-time system information about your Mac. This tool is primarily designed for Mac users who want to experiment with AI and Deep Learning on their machines.

Status: BETA - This project is currently in beta. We're actively looking for feedback to improve functionality and user experience. Please share your thoughts and suggestions!

Why Use It?

  • Provides Claude Desktop or other MCP clients with access to your Mac's hardware specifications, system configuration, and resource usage
  • Enables more targeted and accurate assistance for software optimization and troubleshooting
  • Runs as a secure local API with minimal overhead
  • Only executes safe, verified commands:
    • system_profiler - to gather system information
    • conda - to analyze Python environment configurations

Installation

Method 1: Using UV + Git Clone

Prerequisites
  • Python 3.8 or higher
  • UV package manager installed
Steps
  1. Clone the repository: bash git clone git@github.com:zhongmingyuan/mcp-my-mac.git
  2. Configure for your AI client:[Claude Desktop] Add the following to your MCP server config file:
    "mcpServers": { "mcp-my-mac": { "command": "uv", "args": [ "--directory", "/YOUR_PATH_TO/mcp-my-mac", "run", "-m", "mcp_server_my_mac" ] } }

    Note: Replace /YOUR_PATH_TO with the actual path where you cloned the repository.

    [Cursor] Add tool by selecting "command" in UI:
    uv run --directory /YOUR_PATH_TO/mcp-my-mac mcp_server_my_mac

Usage

After installation, Claude Desktop will automatically connect to this API when running on your Mac, allowing it to access system information when needed for answering your questions or providing assistance.

-
security - not tested
A
license - permissive license
-
quality - not tested

local-only server

The server can only run on the client's local machine because it depends on local resources.

Stop Package Chaos: Unveil Your Mac’s Setup for Targeted ML Debugging

  1. Why Use It?
    1. Installation
      1. Method 1: Using UV + Git Clone
    2. Usage

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