🚀 MCP Windows Automation Server - AI-Powered Windows Control Suite

Transform your Windows PC into an intelligent automation hub controlled by AI assistants.

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🔍 Overview

MCP Windows Automation Server is an AI-native automation framework that allows AI assistants like ChatGPT, Claude, LocalAI, and others to automate over 200 Windows tasks through natural language commands. It uses Model Context Protocol (MCP) to provide deep system-level control securely.

🤖 What is Model Context Protocol (MCP)?

MCP is an open protocol by Anthropic that allows AI models to interact safely with local tools, APIs, and OS services. The MCP Server implements this for Windows, making AI assistants powerful desktop controllers.

• 🔐 Secure OS Command Access
• 🧠 AI Agent Compatibility
• 🔄 Real-Time Communication
• 🔧 Plugin-Ready Framework

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🌟 Key Features

• ✅ 209+ Tools for Automation
• 🧠 AI-Context Awareness
• 🔁 Bi-directional AI ↔️ System
• ⚙️ Sandbox Execution Mode
• 🧱 Modular Plugin Design
• 🧪 ML Engine for Prediction

🧭 Tool Categories

• 🖥️ System Control: Processes, registry, services
• 🧰 UI Automation: Mouse/keyboard emulation, OCR
• 🎵 Media: Spotify, YouTube, VLC automation
• 🌍 Web Automation: Chrome DevTools, form automation
• 📂 File System: Sync, backups, file watchers
• 📑 Office: Excel, Word, PowerPoint, Outlook
• 🖼️ Vision: OCR, screenshot utilities
• 🌐 Networking: WiFi, DNS, firewall, hotspot tools

🧠 AI/ML Prediction Engine

The ML engine observes system usage and user behavior, training predictive models for:

• 🔮 Action Prediction
• 📊 Resource Forecasting
• 🎯 Workflow Optimization
• 🛠️ Performance Tuning

⚡ Use Cases

• 📈 Automate business reports, emails, monitoring
• 🎧 Create playlists, record media actions
• 💻 Developer setup automation
• 🔧 Admin tasks like SFC, event logs, service checks

🚀 Installation

git clone https://github.com/mukul975/mcp-windows-automation.git
cd mcp-windows-automation
pip install -r requirements.txt

▶️ Start Server

python src/unified_server.py

🌐 Web Automation

1. Download ChromeDriver
2. Add to PATH or project root

🧠 ML Monitoring

python -c "from src.unified_server import start_ml_monitoring; start_ml_monitoring()"

🧪 Sample Tool Calls

{
  "tool": "spotify_play_favorite_song"
}
{
"tool": "take_screenshot",
"parameters": { "filename": "screen.png" }
}

📁 Project Structure

├── src/
│   ├── unified_server.py
│   ├── advanced_automation_server.py
│   ├── mcp_gui.py
├── config/
├── docs/
├── examples/
├── tests/
└── README.md

🧪 Testing

python -m pytest tests/

🤝 Contributing

1. Fork and clone
2. Create feature branch
3. Add tests
4. Run tests
5. Submit PR

📜 License

MIT License — See LICENSE file

📬 Contact

Email: [email protected]

GitHub: mukul975

“Automate Everything. With AI.” 🧠💻