
test_mcp
一个使用Claude和VLM技术实现的自动化网站克隆与迭代优化工具。
Repository Info
About This Server
一个使用Claude和VLM技术实现的自动化网站克隆与迭代优化工具。
Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.
Documentation
Self-Improving Website Cloner with Claude VLM
This repository demonstrates a self-improving website cloning system built using Claude. It features an automated iterative refinement loop powered by VLM (Vision Language Model) image comparison.
!Website Cloning System
What We've Built
We've created a comprehensive system that can:
- Clone website structures - Extract layouts, styles and content patterns from websites
- Set up development environments - Create working development copies with proper separation of HTML/CSS/JS
- Automate visual comparison - Use Claude's VLM capabilities to analyze visual differences between versions
- Implement iterative feedback loops - Automatically refine and improve websites based on AI suggestions
- Self-maintain project structures - Handle directory creation, configuration, and dependency management
Components
- CLAUDE.md - Comprehensive documentation with code snippets for integration
- setup_firecrawl_mcp.sh - MCP server setup for website cloning
- update_mcp_servers.py - Self-updating repository of MCP tools
- test_website_clone.js - Website structure extraction tool
- weedth_clone_test.js - Domain-specific example implementation
- implement_iteration_cycle.js - Complete iterative refinement system
Key Features
1. Self-Improving Feedback Loop
The system captures screenshots of the website at different stages, compares them using Claude's VLM capabilities, and automatically implements suggested improvements:
// Extract structured feedback from Claude's VLM analysis
function extractStructuredFeedback(claudeResponse) {
// Process visual differences between website versions
// Generate actionable improvements
// Format as structured data for automated implementation
}
// Apply feedback through automated code changes
async function applyImplementationPlan(plan) {
// Backup current files
// Implement suggested CSS improvements
// Update HTML structure
// Document changes in iteration log
}
2. Automated Project Structure Management
function checkProjectStructure() {
// Verify required directories exist
// Create missing components
// Set up configuration files
// Initialize development environment
}
3. Cross-Domain Adaptability
The system is designed to be easily adapted to different domains:
- E-commerce - Product listings, cart systems, checkout flows
- Education - Course catalogs, learning modules, assessment systems
- Healthcare - Provider directories, appointment booking, patient portals
- Real Estate - Property listings, map integration, filtering systems
Getting Started
- Clone this repository
- Run the initial setup:
./setup_firecrawl_mcp.sh - Launch the iterative cycle implementation:
node implement_iteration_cycle.js - Select option 4 to run the complete cycle
Potential Next Steps
1. True Vision API Integration
Connect to Claude's Vision API for real-time screenshot analysis:
async function analyzeScreenshotWithAPI(imagePath) {
// Send screenshot to Claude Vision API
// Process visual feedback
// Generate structured improvement plan
}
2. Research API Integration
Add capability to research domain-specific best practices:
async function researchDomainPatterns(domain) {
// Query design pattern databases
// Research competitive sites
// Analyze successful implementations
// Generate domain-specific recommendations
}
3. Multi-Tool Orchestration
Coordinate multiple AI tools for specialized functions:
async function orchestrateTools(task) {
// Delegate visual analysis to Claude VLM
// Use code generation models for implementation
// Leverage specialized domain models for content
// Coordinate through central workflow
}
4. Self-Modifying Capabilities
Allow the system to improve its own code:
async function selfOptimize() {
// Analyze own performance metrics
// Identify optimization opportunities
// Implement code improvements
// Test and validate changes
}
Ethical Considerations
This project is designed for ethical website structure extraction. Always:
- Respect website terms of service and robots.txt
- Obtain proper permissions before cloning commercial sites
- Use for educational, development, or authorized purposes only
- Respect copyright and intellectual property
License
MIT
Acknowledgments
- Inspired by a February 21, 2025 X post about website cloning with Claude
- Built with Claude from Anthropic
- Uses MCP server architecture for Claude desktop integration
Quick Start
Clone the repository
git clone https://github.com/j-94/test_mcpInstall dependencies
cd test_mcp
npm installFollow the documentation
Check the repository's README.md file for specific installation and usage instructions.
Repository Details
Recommended MCP Servers
Discord MCP
Enable AI assistants to seamlessly interact with Discord servers, channels, and messages.
Knit MCP
Connect AI agents to 200+ SaaS applications and automate workflows.
Apify MCP Server
Deploy and interact with Apify actors for web scraping and data extraction.
BrowserStack MCP
BrowserStack MCP Server for automated testing across multiple browsers.
Zapier MCP
A Zapier server that provides automation capabilities for various apps.