Windows-MCP: Control Your Computer with Natural Language Commands – The New Era of AI Automation
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Have you ever imagined describing tasks in plain language and watching your computer execute them? Windows-MCP makes this vision a reality. This open-source project acts like your personal digital assistant, transforming natural language instructions into actual computer operations, fundamentally changing human-computer interaction.
🔍 Core Feature Analysis (No Computer Vision Required!)
What makes Windows-MCP unique is its complete departure from traditional screen recognition techniques. Instead, it achieves precise control through direct access to Windows’ underlying data:
Functional Category | Tool Name | Practical Application Scenarios |
---|---|---|
Basic Operations | Click-Tool | Click specific screen coordinates |
Type-Tool | Input text into fields | |
Move-Tool | Move mouse pointer | |
Advanced Control | Shortcut-Tool | Execute key combinations (Ctrl+C, etc.) |
Launch-Tool | Launch applications from Start Menu | |
Shell-Tool | Run PowerShell commands | |
System Interaction | State-Tool | Capture current window state + screenshot |
Clipboard-Tool | Read/write clipboard content | |
Scroll-Tool | Scroll page content |
⚡ Real Performance Data
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Operation latency: 1.5-2.3 seconds per action (measured click-to-click interval) -
Supported systems: Windows 7/8/8.1/10/11 (all versions) -
Technology requirements: Pure Python implementation, no special hardware needed
“The most surprising aspect is that it doesn’t require specialized model training—any LLM can power this system” — Project developer Jeomon George describes the design philosophy
🛠️ Step-by-Step Installation Guide (3 Simple Steps)
Prerequisites
# Essential components list
pip install uv # Astra package manager
npm install -g @anthropic-ai/dxt # Desktop extension component
Installation Workflow
graph TD
A[Clone Repository] --> B[Build Extension]
B --> C[Install in Claude]
C --> D[Start Using]
subgraph Command Details
A -->|git clone https://github.com/CursorTouch/Windows-MCP.git| B
B -->|npx @anthropic-ai/dxt pack| C
C -->|Load .dxt file in Claude Settings| D
end
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Get Source Code
git clone https://github.com/CursorTouch/Windows-MCP.git cd Windows-MCP
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Build Desktop Extension
Run build command to generate.dxt
installation package:npx @anthropic-ai/dxt pack
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Integrate with Claude Desktop
In Claude application:
Settings → Extensions → Install Extension → Select generated .dxt file
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💡 Tip: For integration issues, consult the MCP official documentation containing log review and common solutions
🌟 Real-World Application Scenarios
Case 1: Cross-Application Data Management
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Voice command: “Open Excel and paste quarterly data from email into column B” -
MCP automatically executes: -
Uses Launch-Tool
to start Outlook -
Selects email content with Click-Tool
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Executes Ctrl+C copy with Shortcut-Tool
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Launches Excel and navigates to column B -
Executes Ctrl+V paste with Shortcut-Tool
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Case 2: Web Information Extraction
# Scrape-Tool workflow
When user requests "Get product prices":
1. Activate browser window
2. Identify price element locations
3. Extract text content
4. Return results via Clipboard-Tool
⚠️ Critical Considerations (Must Read Before Use)
Current Technical Limitations
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Text Selection Precision
Due to reliance on a11y accessibility tree, precise selection of specific sentences within paragraphs remains challenging (under development) -
Programming Scenario Adaptation
Type-Tool
works for text input but pastes entire code blocks when programming (optimization upcoming)
Security Warnings
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This tool interacts directly with OS infrastructure. Avoid using in:
Computers with critical business data Work machines with unsaved important documents Devices involved in financial operations
❓ Frequently Asked Questions
Q1: Do I need specific AI models?
No! Windows-MCP works with all LLMs—whether Claude, GPT, or open-source models—as long as they support MCP protocol.
Q2: Does it record my activity data?
The project is fully open-source (MIT license) with transparent code. No data collection features exist.
Q3: Does it support multi-monitor setups?
Yes, coordinate positioning automatically adapts to primary display settings.
Q4: Is commercial use permitted?
MIT license allows commercial use free of charge, only requiring copyright retention.
📚 Technical Deep Dive
Architecture Highlights
graph LR
User[User Command] --> LLM[Language Model]
LLM --> MCP[MCP Protocol Conversion]
MCP --> WinAPI[Windows System Calls]
WinAPI --> Action[Execute Actions]
Core Component Workflow:
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User provides natural language instruction -
LLM parses intent and generates MCP command set -
DXT extension converts commands to system-level operations -
Executes specific actions via Windows API -
Returns results to user
Performance Optimization Keys
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Memory Management: Python 3.13+ memory optimization reduces resource consumption -
Parallel Processing: Asynchronous screenshot and UI analysis -
Caching Mechanism: Window state data reuse minimizes duplicate collection
🏆 Project Impact Tracker
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Gained 800+ stars within six months of open-sourcing. Now included in Anthropic’s official recommended tools.
🤝 Join the Developer Community
# Contribution steps:
+ 1. Fork main repository
+ 2. Create feature branch (feat/xxx)
+ 3. Submit Pull Request
+ 4. Merge after CI testing
Detailed guidelines in CONTRIBUTING documentation
📜 Academic Citation Format
@software{
author = {George, Jeomon},
title = {Windows-MCP: Lightweight open-source project for integrating LLM agents with Windows},
year = {2024},
publisher = {GitHub},
url={https://github.com/CursorTouch/Windows-MCP}
}
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Project creator Jeomon emphasizes: “Our goal is to make AI a true productivity partner, not a tech demo gimmick”
Final Reminder: Technological innovation carries inherent risks. Always verify operations in test environments first. This evolving project receives weekly updates—regularly execute git pull
to stay current! 🚀