Based on a tutorial by Eduards Ruzga
If you’ve ever wished Claude AI could directly manipulate files on your computer, create projects, and run commands without you constantly copying and pasting code, you’re not alone.
I recently discovered Desktop Commander through Edward’s excellent tutorial, and I’m excited to break down this powerful MCP tool that’s changing how we work with AI. This summary will help you understand what Desktop Commander can do and whether it’s worth watching the full video.
Quick Navigation
- What is Desktop Commander? (00:00-05:30)
- Live Demo: Creating an Animated Web Page (05:31-12:45)
- Desktop Commander vs Cursor/Windsurf (12:46-18:20)
- Understanding MCP: The Container Analogy (18:21-25:00)
- Real-world Usage and Growth Stats (25:01-32:30)
- Security Considerations for Non-technical Users (32:31-38:15)
- Bonus: Camera Gesture Drawing Project (38:16-44:00)
- Tips, Tricks, and Future Roadmap (44:01-End)
What is Desktop Commander?
Desktop Commander is an open-source MCP (Model Context Protocol) tool that transforms Claude AI from a simple chat interface into a powerful computer automation assistant. Instead of just generating text responses, Claude can actually interact with your local files and system.
Key Capabilities:
- Adds 18 different tools to Claude’s capabilities
- Reads, writes, and manipulates local files
- Runs terminal commands and processes
- Creates complete projects and opens them in browsers
- Works with any file type or programming language
My Take:
The installation process is remarkably simple – just one line of code through npm. What impressed me most is how this tool bridges the gap between AI assistance and actual computer control, something that felt like science fiction just a year ago.
Live Demo: Creating an Animated Web Page
Edward demonstrates Desktop Commander’s power by asking Claude to “create an animated hello Angel and Edward web page in user folder and then open it in browser.” The AI doesn’t just provide code – it actually creates the files and launches the result.
What Happens Behind the Scenes:
- Claude checks the system configuration
- Creates a new directory in the specified folder
- Writes HTML, CSS, and JavaScript files
- Automatically opens the finished page in the browser
- Can make real-time modifications based on feedback
When they wanted to change the romantic hearts theme to something more professional with fireworks, Claude immediately rewrote the code and updated the files. The AI even took creative liberty by adding a subscribe button (though it didn’t link anywhere).
My Take:
This workflow feels incredibly natural compared to traditional coding. Instead of managing multiple files and browser refreshes, you’re having a conversation about what you want, and the AI handles all the technical execution.
Desktop Commander vs Cursor/Windsurf
Edward shares an unexpected discovery: despite being a paid Windsurf subscriber, he found Desktop Commander more effective for his workflow. This surprised him because Windsurf and Cursor are specifically designed as AI-powered code editors.
Why Desktop Commander Works Better:
- Less “opinionated” – not constrained to coding-specific solutions
- Better for “wide coding” – creating diverse types of content
- Can handle non-coding tasks like creating diagrams and artifacts
- Works as a “less closed box” with fewer limitations
- Users report better results even for pure coding tasks
My Take:
The “coding box” vs “open box” analogy resonates strongly. Traditional AI coding tools assume you want to code everything, while Desktop Commander lets Claude choose the best approach for each task – whether that’s code, diagrams, or direct file manipulation.
Understanding MCP: The Container Analogy
Edward explains MCP using a brilliant shipping container analogy. Before standardized containers, international shipping required different trucks for different cargo types. MCP creates the same standardization for AI tools.
How MCP Works:
- MCP packages tools in a standardized format
- Any AI application supporting MCP can use all MCP tools
- Solves the “cold start” problem of building custom integrations
- Creates an ecosystem where tools work across different AI platforms
- Claude is the “boat,” Desktop Commander is a “container”
This standardization means that tools built for one MCP-compatible platform automatically work with others, creating a powerful ecosystem of AI capabilities.
Real-world Usage and Growth Stats
The growth numbers are impressive. Desktop Commander has been downloaded 57,000 times in a single month through npm, with 436,000+ monthly tool calls tracked on Smithery.ai.
Usage Statistics:
- 57,000 monthly downloads via npm
- 436,000+ monthly tool calls
- 220,000 commands executed in just a couple of weeks
- 94,000 files read in the same period
- Growth exploded in March 2025 after months of slow adoption
My Take:
The fact that they’re hitting million-event limits on their analytics free tier every four days shows this isn’t just curiosity-driven usage – people are actively building real projects with this tool.
One standout user story involves a business owner who used Desktop Commander to update a three-year-old business management tool he’d built but couldn’t maintain. Within hours, he was adding features he’d wanted for years.
Security Considerations for Non-technical Users
Angela raises an important question about security for non-technical users publishing applications. Edward provides honest guidance about the current limitations and alternatives.
Security Guidelines:
- Static web pages and personal projects are generally safe
- Security concerns arise with databases and user authentication
- Desktop Commander doesn’t provide built-in security guardrails
- Consider platforms like Lovable for more restricted but safer environments
- No current tool offers 100% security guarantees
My Take:
Edward’s honesty about security limitations is refreshing. Rather than overselling the tool’s safety, he clearly explains where Desktop Commander works well (personal projects, static sites) and where additional caution is needed (database-driven applications).
Bonus: Camera Gesture Drawing Project
Edward showcases a fascinating side project: a web application that lets you draw in the air using camera gestures. The drawing gets thicker as you move closer to the camera, creating an intuitive 3D-like experience.
Technical Highlights:
- Uses computer vision libraries for gesture detection
- Real-time drawing response to hand movements
- Depth-aware line thickness based on distance from camera
- Built using existing gesture recognition libraries
- Can be adapted for music creation and other interactive applications
The demo shows Desktop Commander’s versatility beyond traditional coding – it can integrate with computer vision, audio libraries, and create entirely new types of interactive experiences.
Tips, Tricks, and Future Roadmap
Edward shares practical advice for getting the most out of Desktop Commander, along with insights into where the project is heading.
Best Practices:
- Break large projects into smaller, manageable parts
- Split big files into multiple smaller files for easier AI manipulation
- Use version control (Git) to enable easy rollbacks when AI makes mistakes
- Ask Claude to set up version control for your projects
- Think like a software architect – plan the structure before diving in
Future Roadmap Considerations:
- Native rollback functionality
- Better support for PDF and CSV files
- Custom client with improved UX
- Browser integration and UI manipulation
- Mobile development capabilities
My Take:
The emphasis on breaking problems down into smaller parts is crucial. Even with AI assistance, good software engineering principles still apply – the AI just makes the execution much faster and more accessible to non-programmers.
