Portable MCP Web Scraper

Portable MCP Web Scraper

Efficient web scraping MCP server with a two-step workflow for token-efficient content extraction. Supports previewing HTML structure, targeted scraping, and entire documentation site crawling.

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README

🚀 Portable MCP Web Scraper

A drop-in MCP (Model Context Protocol) server for efficient web scraping with two-step workflow optimization.

✨ Features

  • Two-Step Workflow: Get HTML structure preview first, then scrape with targeted filters
  • Token Efficient: Minimal token usage for AI analysis and decision-making
  • Clean Output: Automatically removes navigation, ads, and UI elements
  • Portable: Drop anywhere and add to your MCP servers
  • Multiple Tools: Single page, multi-page, and documentation site scraping

🚀 Quick Start

Option 1: Automated Installation

python install.py

Option 2: Manual Setup

  1. Install dependencies:

    pip install -r requirements.txt
    
  2. Copy to your MCP servers directory:

    cp portable_mcp_scraper.py /path/to/your/mcp/servers/
    
  3. Add to your MCP configuration (e.g., ~/.cursor/mcp.json):

    {
      "mcpServers": {
        "web-scraper": {
          "command": "python",
          "args": ["/path/to/your/mcp/servers/portable_mcp_scraper.py"]
        }
      }
    }
    
  4. Restart your MCP client

🛠️ Available Tools

1. preview_html_structure

Get a clean HTML structure preview for AI analysis.

Parameters:

  • url (string): The URL to analyze
  • max_elements (int, optional): Maximum elements to include (default: 50)

Returns: Structured HTML preview with minimal text content

2. scrape_web_content

Scrape web content with custom filtering.

Parameters:

  • url (string): The URL to scrape
  • include_tags (list, optional): HTML tags to include
  • exclude_tags (list, optional): HTML tags to exclude
  • save_to_file (bool, optional): Save content to file (default: false)
  • output_dir (string, optional): Directory to save files (default: "./scraped_content")

Returns: Clean Markdown content

3. scrape_documentation_site

Scrape an entire documentation site with intelligent crawling.

Parameters:

  • base_url (string): Base URL of the documentation site
  • max_pages (int, optional): Maximum pages to scrape (default: 10)
  • include_tags (list, optional): HTML tags to include
  • exclude_tags (list, optional): HTML tags to exclude
  • save_to_files (bool, optional): Save each page to separate file (default: true)
  • output_dir (string, optional): Directory to save files (default: "./documentation")

Returns: Summary of scraped content with file paths

💡 Two-Step Workflow Benefits

  1. Step 1: Get HTML structure preview (~500-1000 tokens)
  2. Step 2: Scrape with AI-determined filters (clean, focused content)

Efficiency Gains:

  • For 100-page documentation: ~90% token reduction
  • AI only analyzes structure, not full content
  • Clean, focused output without manual filtering
  • Massive cost savings for large documentation sites

🧪 Testing

Run the test script to verify everything works:

python test_mcp_server.py

📋 Example Usage

Basic Single Page Scraping

# Get structure preview first
preview = preview_html_structure("https://cursor.com/docs")

# Then scrape with filters
content = scrape_web_content(
    url="https://cursor.com/docs",
    include_tags=["h1", "h2", "h3", "p", "div"],
    exclude_tags=["nav", "footer", "aside"],
    save_to_file=True
)

Documentation Site Scraping

# Scrape entire documentation site
summary = scrape_documentation_site(
    base_url="https://cursor.com/docs",
    max_pages=20,
    save_to_files=True,
    output_dir="./cursor_docs"
)

🔧 Requirements

  • Python 3.8+
  • Google Chrome browser
  • ChromeDriver (automatically managed by webdriver-manager)

📁 Files

  • portable_mcp_scraper.py - The main MCP server
  • fastmcp.json - FastMCP configuration
  • install.py - Automated installation script
  • test_mcp_server.py - Test script
  • requirements.txt - Python dependencies
  • USAGE_GUIDE.md - 📚 Complete usage guide with examples
  • PORTABLE_PACKAGE.md - Detailed package information
  • SUCCESS_SUMMARY.md - What this package provides

🎯 Perfect For

  • AI Agents that need to scrape documentation on-demand
  • Documentation Analysis with minimal token usage
  • Content Extraction from complex websites
  • Multi-page Scraping with intelligent crawling
  • Cost-Effective web scraping for AI workflows

📄 License

MIT License - Feel free to use and modify as needed.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📞 Support

If you encounter any issues:

  1. Check that Google Chrome is installed
  2. Verify all dependencies are installed
  3. Run the test script to diagnose problems
  4. Check the documentation files for troubleshooting

Ready to drop and use! 🎉

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