What is Mcp Windows Website Downloader

mcp-windows-website-downloader is an MCP tool designed to download entire Windows documentation websites and their assets, organizing them for AI use, particularly for RAG indexing.

Use cases

Use cases include downloading technical documentation for software projects, archiving educational materials for machine learning applications, and preparing website content for analysis and indexing in AI systems.

How to use

To use mcp-windows-website-downloader, clone the repository, set up a virtual environment, install the necessary packages, and configure the command in your claude_desktop_config.json. Then, you can start the server and call the download tool with the desired URL.

Key features

Key features include the ability to download complete documentation sites, maintain a basic link structure, organize assets like CSS, JS, and images, and create an index for RAG systems.

Where to use

mcp-windows-website-downloader can be used in fields such as software documentation, educational resources, and any scenario where comprehensive website content needs to be archived for AI processing.

MCP Website Downloader

Simple MCP server for downloading documentation websites and preparing them for RAG indexing.

Features

• Downloads complete documentation sites, well big chunks anyway.
• Maintains link structure and navigation, not really. lol
• Downloads and organizes assets (CSS, JS, images), but isn’t really AI friendly and it all probably needs some kind of parsing or vectorizing into a db or something.
• Creates clean index for RAG systems, currently seems to make an index in each folder, not even looked at it.
• Simple single-purpose MCP interface, yup.

Installation

Fork and download, cd to the repository.

uv venv
./venv/Scripts/activate
pip install -e .

Put this in your claude_desktop_config.json with your own paths:

Other Usage you don’t need to worry about and may be hallucinatory lol:

1. Start the server:

python -m mcp_windows_website_downloader.server --library docs_library

2. Use through Claude Desktop or other MCP clients:

result = await server.call_tool("download", {
    "url": "https://docs.example.com"
})

Output Structure

docs_library/
  domain_name/
    index.html
    about.html
    docs/
      getting-started.html
      ...
    assets/
      css/
      js/
      images/
      fonts/
    rag_index.json

Development

The server follows standard MCP architecture:

src/
  mcp_windows_website_downloader/
    __init__.py
    server.py    # MCP server implementation
    core.py      # Core downloader functionality
    utils.py     # Helper utilities

Components

• server.py: Main MCP server implementation that handles tool registration and requests
• core.py: Core website downloading functionality with proper asset handling
• utils.py: Helper utilities for file handling and URL processing

Design Principles

1. Single Responsibility

   • Each module has one clear purpose
   • Server handles MCP interface
   • Core handles downloading
   • Utils handles common operations

2. Clean Structure

   • Maintains original site structure
   • Organizes assets by type
   • Creates clear index for RAG systems

3. Robust Operation

   • Proper error handling
   • Reasonable depth limits
   • Asset download verification
   • Clean URL/path processing

RAG Index

The rag_index.json file contains:

{
  "url": "https://docs.example.com",
  "domain": "docs.example.com",
  "pages": 42,
  "path": "/path/to/site"
}

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

License

MIT License - See LICENSE file

Error Handling

The server handles common issues:

• Invalid URLs
• Network errors
• Asset download failures
• Malformed HTML
• Deep recursion
• File system errors

Error responses follow the format:

{
  "status": "error",
  "error": "Detailed error message"
}

Success responses:

{
  "status": "success",
  "path": "/path/to/downloaded/site",
  "pages": 42
}