No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by claude-did-this · MCP Server · ★ 332
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is MCPControl safe to install? View the security audit →
MCPControl Windows control server for the Model Context Protocol, providing programmatic control over system operations including mouse, keyboard, window management, and screen capture functionality. Note: This project currently supports Windows only. 🔥 Why MCPControl? MCPControl bridges the gap between AI models and your desktop, enabling secure, programmatic control of: 🖱️ Mouse movements and clicks ⌨️ Keyboard input and shortcuts 🪟 Window management 📸 Screen capture and analysis 📋 Clipboard operations 🔌 Quick Start Prerequisites Install Build Tools (including VC++ workload) Install Python (if not already installed) Install Node.js powershell # Install latest LT
| Stars | 332 |
| Forks | 50 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 73.4345105578102/100 |
| Open Issues | 42 |
| Last Updated | 2025-12-02 |
| Created | 2024-12-03 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~120k |
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MCPControl is MCP server for Windows OS automation. It is categorized as a MCP Server with 332 GitHub stars.
MCPControl is primarily written in TypeScript. It covers topics such as ai, claude, computer-control.
You can find installation instructions and usage details in the MCPControl GitHub repository at github.com/claude-did-this/MCPControl. The project has 332 stars and 50 forks, indicating an active community.
MCPControl is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to MCPControl on Agent Skills Hub include os-ai-computer-use, toolhive-studio, amical. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: