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Terminate Processes with Natural Language

Cross-platform MCP server that exposes tools to list and kill OS processes via natural language, with filtering by CPU, memory, user, and name.


11
Spark score
out of 100
Status Verified Official
Updated 4 months ago
Version 1.0.0
Models

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Why it matters

Effortlessly manage and terminate system processes using natural language commands. Ideal for identifying and stopping resource-hogging applications without complex command-line interactions.

Outcomes

What it gets done

01

View running processes with detailed filtering by name, user, and resource usage.

02

Terminate specific processes identified through natural language queries.

03

Sort processes by CPU or memory consumption to pinpoint performance issues.

04

Filter processes based on system or user context.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-kill-process-mcp | bash

Capabilities

Tools your agent gets

process_list

Displays running processes sorted by CPU or memory with optional filtering by name, user, status, and thresholds.

process_kill

Terminates the selected process.

Overview

kill-process-mcp server

What it does

A Model Context Protocol server that lets LLMs list and terminate operating system processes through natural language queries, with support for sorting, filtering, and threshold-based selection.

How it connects

Use this when you want to give your AI assistant direct access to system process management-helpful for identifying resource-hungry applications, troubleshooting performance bottlenecks, or terminating unresponsive processes without switching to a terminal or task manager.

Source README

kill-process-mcp ๐Ÿ”ซ

GitHub Stars License Last Commit Maintenance

Cross-platform MCP (Model Context Protocol) server exposing LLM-accessible tools to list and kill OS processes via natural language queries.

Perfect for shy ninjas who just want rogue processes gone: "Find and nuke the damn CPU glutton choking my system!"

Demo

kill-process-mcp-demo

Tools

The following tools are exposed to MCP clients:

  • process_list: Lists running processes sorted by CPU or memory with optional name, user, status, CPU/memory thresholds, system-process filtering, sort order and limit
  • process_kill: Terminates the selected process (with extreme prejudice!)

Requirements

  • MCP-compatible LLM client (like Claude Desktop or Cursor)
  • OS: macOS/Windows/Linux
  • Python 3.13 or higher
  • uv
  • Libraries: mcp psutil

Installation

You can install kill-process-mcp in two ways:

  1. Preferred: use uvx - no cloning or setup needed.
  2. Alternative: clone the repo and set up manually.

1. Install uv (required for both methods)

Install uv if missing:

pip install uv

# or on macOS:
brew install uv

In case of the preferred uvx method you can now configure your MCP client (skip the cloning step below).

2. Clone the repo and install (only required for alternative mode, skip for uvx)

git clone https://github.com/misiektoja/kill-process-mcp.git
cd kill-process-mcp

Install dependencies:

uv sync

3. Configure MCP Client


๐ŸŸฃ Claude Desktop

Register the kill-process-mcp as an MCP server in Claude Desktop.

Add the following to claude_desktop_config.json file if you want to use uvx method (recommended):

{
    "mcpServers": {
        "kill-process-mcp": {
            "command": "uvx",
            "args": ["kill-process-mcp@latest"]
        }
    }
}

In case of an alternative manual method using a cloned repo:

{
    "mcpServers": {
        "kill-process-mcp": {
            "command": "uv",
            "args": [
                "run",
                "--directory",
                "/path/to/kill-process-mcp",
                "kill_process_mcp.py"
            ]
        }
    }
}

Default claude_desktop_config.json location (if the file is missing - create it):

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Replace /path/to/kill-process-mcp with the actual path of your project folder (remember to escape backslash characters if you're on Windows, e.g.: C:\\path\\to\\kill-process-mcp)

Restart Claude Desktop and it should be able to talk to the kill-process-mcp server.

You can check if the server is loaded by going to Profile โ†’ Settings โ†’ Connectors.


๐ŸŸข Cursor

Register the kill-process-mcp as an MCP server in Cursor.

Open Cursor settings and click Tools & MCP โ†’ Add Custom MCP.

Once the mcp.json file opens, add the following if you want to use uvx method (recommended):

{
    "mcpServers": {
        "kill-process-mcp": {
            "command": "uvx",
            "args": ["kill-process-mcp@latest"]
        }
    }
}

In case of an alternative manual method using a cloned repo:

{
    "mcpServers": {
        "kill-process-mcp": {
            "command": "uv",
            "args": [
                "run",
                "--directory",
                "/path/to/kill-process-mcp",
                "kill_process_mcp.py"
            ]
        }
    }
}

Default mcp.json location:

  • macOS/Linux: ~/.cursor/mcp.json
  • Windows: %USERPROFILE%\.cursor\mcp.json

Replace /path/to/kill-process-mcp with the actual path of your project folder (remember to escape backslash characters if you're on Windows, e.g.: C:\\path\\to\\kill-process-mcp)

You should be able to talk to the kill-process-mcp server now.

You can check if the server is loaded by going to Cursor settings and clicking Tools & MCP.


Optional: Install a Persistent Shim

If you prefer faster startup or offline use while using the uvx method, you can install a local shim once:

uv tool install kill-process-mcp

Then change your LLM client config to:

{
  "mcpServers": {
    "kill-process-mcp": {
      "command": "kill-process-mcp"
    }
  }
}

Example Hit Contracts

Here are some example prompts you can use with your MCP-compatible AI assistant when interacting with this MCP server:

  • Kill the damn process slowing down my system!
  • Check my top 5 CPU parasites and flag any that look like malware
  • List the 3 greediest processes by RAM usage
  • Exterminate every process with Spotify in its name
  • List Alice's Python processes, max 10 entries
  • Which processes are over 2% CPU and 100 MB RAM
  • anything else your imagination brings ...

Upgrade

When using uvx, it automatically fetches and runs the latest published version each time your LLM client starts.

If you're using the alternative manual method with a cloned repo, update with:

cd kill-process-mcp
git pull
uv sync --reinstall

Known issues

We do not pin Python. New minor versions are usually supported on day one via wheels.

If you're using the alternative manual method with a cloned repo and you hit a build error (e.g pydantic-core or rpds-py failing with a Rust toolchain message), it usually means the ecosystem is catching up with the latest Python version. In most cases this is temporary and fixed shortly by
upstream packages.

Try a clean rebuild in such case:

cd kill-process-mcp
rm -rf .venv
uv sync

If that still fails, temporarily use your previous Python minor version until compatible wheels are published (typically within a few days).

Change Log

See RELEASE_NOTES.md for details.

FAQ

Common questions

Discussion

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