Pratyay/mac-monitor-mcp
Platform-specific configuration:
{
"mcpServers": {
"mac-monitor-mcp": {
"command": "npx",
"args": [
"-y",
"mac-monitor-mcp"
]
}
}
}Add the config above to .claude/settings.json under the mcpServers key.
[](https://archestra.ai/mcp-catalog/pratyay__mac-monitor-mcp)
A Model Context Protocol (MCP) server that identifies resource-intensive processes on macOS across CPU, memory, and network usage.
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.
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 git clone https://github.com/Pratyay/mac-monitor-mcp.git
cd mac-monitor-mcp python -m venv venv
source venv/bin/activate pip install mcpIf you installed globally with uv:
mac-monitorIf you're running from the project directory:
python src/mac_monitor/monitor.pyOr using uv run (from project directory):
uv run mac-monitorYou 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.
The server exposes three tools:
get_resource_intensive_processes()Returns informati
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