MacOS Resource Monitor MCP Server

A Model Context Protocol (MCP) server that identifies resource-intensive processes on macOS across CPU, memory, and network usage.

Hosted deployment

A hosted deployment is available on Fronteir AI.

Overview

MacOS Resource Monitor is a lightweight MCP server that exposes an MCP endpoint for monitoring system resources. It analyzes CPU, memory, and network usage, and identifies the most resource-intensive processes on your Mac, returning data in a structured JSON format.

Requirements

• macOS operating system
• Python 3.10+
• MCP server library

Installation

Option 1: Global Installation (Recommended)

Install the MCP server globally using uv for system-wide access:

git clone https://github.com/Pratyay/mac-monitor-mcp.git
cd mac-monitor-mcp
uv tool install .

Now you can run the server from anywhere:

mac-monitor

Option 2: Development Installation

1. Clone this repository:

   git clone https://github.com/Pratyay/mac-monitor-mcp.git
   cd mac-monitor-mcp
   

2. Create a virtual environment (recommended):

   python -m venv venv
   source venv/bin/activate  
   

3. Install the required dependencies:

   pip install mcp
   

Usage

Global Installation

If you installed globally with uv:

mac-monitor

Development Installation

If you’re running from the project directory:

python src/mac_monitor/monitor.py

Or using uv run (from project directory):

uv run mac-monitor

You should see the message:

Simple MacOS Resource Monitor MCP server starting...
Monitoring CPU, Memory, and Network resource usage...

The server will start and expose the MCP endpoint, which can be accessed by an LLM or other client.

Available Tools

The server exposes three tools:

1. get_resource_intensive_processes()

Returns information about the top 5 most resource-intensive processes in each category (CPU, memory, and network).

2. get_processes_by_category(process_type, page=1, page_size=10, sort_by="auto", sort_order="desc")

Returns all processes in a specific category with advanced filtering, pagination, and sorting options.

Parameters:

• process_type: "cpu", "memory", or "network"
• page: Page number (starting from 1, default: 1)
• page_size: Number of processes per page (default: 10, max: 100)
• sort_by: Sort field - "auto" (default metric), "pid", "command", or category-specific fields:
  • CPU: "cpu_percent", "pid", "command"
  • Memory: "memory_percent", "resident_memory_kb", "pid", "command"
  • Network: "network_connections", "pid", "command"
• sort_order: "desc" (default) or "asc"

Example Usage: