developer-tools

Computer Control

ab498

by ab498

Automate desktop tasks with Computer Control: mouse, keyboard, screenshots, OCR & window management. Power Automate Desk

Enables desktop automation through mouse control, keyboard input, screenshots, OCR, and window management for direct interaction with graphical user interfaces

github stars

120

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Zero external dependenciesBuilt-in OCR capabilityDirect GUI interaction

best for

  • / Desktop automation and testing
  • / GUI workflow automation
  • / Screen scraping and data extraction
  • / Repetitive task automation

capabilities

  • / Control mouse movements and clicks
  • / Send keyboard input and keystrokes
  • / Take desktop screenshots
  • / Extract text from images using OCR
  • / Manage windows and applications
  • / Automate GUI interactions

what it does

Provides desktop automation capabilities including mouse control, keyboard input, screen capture, and OCR text recognition. Works directly with your computer's GUI without external dependencies.

about

Computer Control is a community-built MCP server published by ab498 that provides AI assistants with tools and capabilities via the Model Context Protocol. Automate desktop tasks with Computer Control: mouse, keyboard, screenshots, OCR & window management. Power Automate Desk It is categorized under developer tools.

how to install

You can install Computer Control in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Computer Control is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Computer Control MCP

MCP server that provides computer control capabilities, like mouse, keyboard, OCR, etc. using PyAutoGUI, RapidOCR, ONNXRuntime. Similar to 'computer-use' by Anthropic. With Zero External Dependencies.

<div align="center" style="text-align:center;font-family: monospace; display: flex; align-items: center; justify-content: center; width: 100%; gap: 10px"> <a href="https://nextjs-boilerplate-ashy-nine-64.vercel.app/demo-computer-control"><img src="https://komarev.com/ghpvc/?username=AB498&label=DEMO&style=for-the-badge&color=CC0000" /></a> <a href="https://discord.gg/ZeeqSBpjU2"><img src="https://img.shields.io/discord/1095854826786668545?style=for-the-badge&color=0000CC" alt="Discord"></a> <a href="https://img.shields.io/badge/License-MIT-yellow.svg"><img src="https://img.shields.io/badge/License-MIT-yellow.svg?style=for-the-badge&color=00CC00" alt="License: MIT"></a> <a href="https://pypi.org/project/computer-control-mcp"><img src="https://img.shields.io/pypi/v/computer-control-mcp?style=for-the-badge" alt="PyPi"></a> </div>

MCP Computer Control Demo

Quick Usage (MCP Setup Using uvx)

Note: Running uvx computer-control-mcp@latest for the first time will download python dependencies (around 70MB) which may take some time. Recommended to run this in a terminal before using it as MCP. Subsequent runs will be instant.

{
  "mcpServers": {
    "computer-control-mcp": {
      "command": "uvx",
      "args": ["computer-control-mcp@latest"]
    }
  }
}

OR install globally with pip:

pip install computer-control-mcp

Then run the server with:

computer-control-mcp # instead of uvx computer-control-mcp, so you can use the latest version, also you can `uv cache clean` to clear the cache and `uvx` again to use latest version.

Features

  • Control mouse movements and clicks
  • Type text at the current cursor position
  • Take screenshots of the entire screen or specific windows with optional saving to downloads directory
  • Extract text from screenshots using OCR (Optical Character Recognition)
  • List and activate windows
  • Press keyboard keys
  • Drag and drop operations
  • Enhanced screenshot capture for GPU-accelerated windows (Windows only)

Note on GPU-accelerated Windows

Traditional screenshot methods like GDI/PrintWindow fail to capture GPU-accelerated windows, resulting in black screens. This impacts games, media players, Electron apps, browsers with GPU acceleration, streaming software, and CAD tools. Use WGC through take_screenshot tool's flag or ENV variable

Configuration

Custom Screenshot Directory

By default, screenshots are saved to the OS downloads directory. You can customize this by setting the COMPUTER_CONTROL_MCP_SCREENSHOT_DIR environment variable:

{
  "mcpServers": {
    "computer-control-mcp": {
      "command": "uvx",
      "args": ["computer-control-mcp@latest"],
      "env": {
        "COMPUTER_CONTROL_MCP_SCREENSHOT_DIR": "C:\Users\YourName\Pictures\Screenshots"
      }
    }
  }
}

Or set it system-wide:

# Windows (PowerShell)
$env:COMPUTER_CONTROL_MCP_SCREENSHOT_DIR = "C:\Users\YourName\Pictures\Screenshots"

# macOS/Linux
export COMPUTER_CONTROL_MCP_SCREENSHOT_DIR="/home/yourname/Pictures/Screenshots"

If the specified directory doesn't exist, the server will fall back to the default downloads directory.

Automatic WGC for Specific Windows

You can configure the system to automatically use Windows Graphics Capture (WGC) for specific windows by setting the COMPUTER_CONTROL_MCP_WGC_PATTERNS environment variable. This variable should contain comma-separated patterns that match window titles:

{
  "mcpServers": {
    "computer-control-mcp": {
      "command": "uvx",
      "args": ["computer-control-mcp@latest"],
      "env": {
        "COMPUTER_CONTROL_MCP_WGC_PATTERNS": "obs, discord, game, steam"
      }
    }
  }
}

Or set it system-wide:

# Windows (PowerShell)
$env:COMPUTER_CONTROL_MCP_WGC_PATTERNS = "obs, discord, game, steam"

# macOS/Linux
export COMPUTER_CONTROL_MCP_WGC_PATTERNS="obs, discord, game, steam"

When this variable is set, any window whose title contains any of the specified patterns will automatically use WGC for screenshot capture, eliminating black screens for GPU-accelerated applications.

Available Tools

Mouse Control

  • click_screen(x: int, y: int): Click at specified screen coordinates
  • move_mouse(x: int, y: int): Move mouse cursor to specified coordinates
  • drag_mouse(from_x: int, from_y: int, to_x: int, to_y: int, duration: float = 0.5): Drag mouse from one position to another
  • mouse_down(button: str = "left"): Hold down a mouse button ('left', 'right', 'middle')
  • mouse_up(button: str = "left"): Release a mouse button ('left', 'right', 'middle')

Keyboard Control

  • type_text(text: str): Type the specified text at current cursor position
  • press_key(key: str): Press a specified keyboard key
  • key_down(key: str): Hold down a specific keyboard key until released
  • key_up(key: str): Release a specific keyboard key
  • press_keys(keys: Union[str, List[Union[str, List[str]]]]): Press keyboard keys (supports single keys, sequences, and combinations)

Screen and Window Management

  • take_screenshot(title_pattern: str = None, use_regex: bool = False, threshold: int = 60, scale_percent_for_ocr: int = None, save_to_downloads: bool = False, use_wgc: bool = False): Capture screen or window
  • take_screenshot_with_ocr(title_pattern: str = None, use_regex: bool = False, threshold: int = 10, scale_percent_for_ocr: int = None, save_to_downloads: bool = False): Extract adn return text with coordinates using OCR from screen or window
  • get_screen_size(): Get current screen resolution
  • list_windows(): List all open windows
  • activate_window(title_pattern: str, use_regex: bool = False, threshold: int = 60): Bring specified window to foreground
  • wait_milliseconds(milliseconds: int): Wait for a specified number of milliseconds

Development

Setting up the Development Environment

# Clone the repository
git clone https://github.com/AB498/computer-control-mcp.git
cd computer-control-mcp

# Build/Run:

# 1. Install in development mode | Meaning that your edits to source code will be reflected in the installed package.
pip install -e .

# Then Start server | This is equivalent to `uvx computer-control-mcp@latest` just the local code is used
computer-control-mcp

# -- OR --

# 2. Build after `pip install hatch` | This needs version increment in orer to reflect code changes
hatch build

# Windows
$latest = Get-ChildItem .\dist\*.whl | Sort-Object LastWriteTime -Descending | Select-Object -First 1
pip install $latest.FullName --upgrade 

# Non-windows
pip install dist/*.whl --upgrade

# Run
computer-control-mcp

Running Tests

python -m pytest

API Reference

See the API Reference for detailed information about the available functions and classes.

License

MIT

For more information or help

FAQ

What is the Computer Control MCP server?
Computer Control is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Computer Control?
This profile displays 36 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.636 reviews
  • Nikhil Garcia· Dec 28, 2024

    Computer Control is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Mateo Singh· Dec 16, 2024

    Computer Control reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Sofia Smith· Dec 12, 2024

    We wired Computer Control into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Ganesh Mohane· Dec 4, 2024

    We evaluated Computer Control against two servers with overlapping tools; this profile had the clearer scope statement.

  • Sakshi Patil· Nov 23, 2024

    Computer Control has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Nikhil Sethi· Nov 19, 2024

    According to our notes, Computer Control benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Alexander Gill· Nov 7, 2024

    I recommend Computer Control for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Amina Jain· Oct 26, 2024

    Strong directory entry: Computer Control surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Chaitanya Patil· Oct 14, 2024

    According to our notes, Computer Control benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Jin Anderson· Oct 10, 2024

    Computer Control has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

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