j-94
MCP Serverj-94public

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。

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JavaScript
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MIT License
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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:

  1. Clone website structures - Extract layouts, styles and content patterns from websites
  2. Set up development environments - Create working development copies with proper separation of HTML/CSS/JS
  3. Automate visual comparison - Use Claude's VLM capabilities to analyze visual differences between versions
  4. Implement iterative feedback loops - Automatically refine and improve websites based on AI suggestions
  5. 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

  1. Clone this repository
  2. Run the initial setup:
    ./setup_firecrawl_mcp.sh
    
  3. Launch the iterative cycle implementation:
    node implement_iteration_cycle.js
    
  4. 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

1

Clone the repository

git clone https://github.com/j-94/test_mcp
2

Install dependencies

cd test_mcp
npm install
3

Follow the documentation

Check the repository's README.md file for specific installation and usage instructions.

Repository Details

Ownerj-94
Repotest_mcp
LanguageJavaScript
LicenseMIT License
Last fetched8/10/2025

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