jmh108 md webcrawl mcp

A Python-based MCP (https://modelcontextprotocol.io/introduction) web crawler for extracting and saving website content.

• Extract website content and save as markdown files
• Map website structure and links
• Batch processing of multiple URLs
• Configurable output directory

1. Clone the repository:

git clone https://github.com/yourusername/webcrawler.git
cd webcrawler

1. Install dependencies:

pip install -r requirements.txt

1. Optional: Configure environment variables:

export OUTPUT_PATH=./output  # Set your preferred output directory

Crawled content is saved in markdown format in the specified output directory.

The server can be configured through environment variables:

• OUTPUT_PATH: Default output directory for saved files
• MAX_CONCURRENT_REQUESTS: Maximum parallel requests (default: 5)
• REQUEST_TIMEOUT: Request timeout in seconds (default: 30)

Install with FastMCP fastmcp install server.py

or user custom settings to run with fastmcp directly

"Crawl Server": {
      "command": "fastmcp",
      "args": [
        "run",
        "/Users/mm22/Dev_Projekte/servers-main/src/Webcrawler/server.py"
      ],
      "env": {
        "OUTPUT_PATH": "/Users/user/Webcrawl"
      }

fastmcp dev server.py --with-editable .

It helps to use https://modelcontextprotocol.io/docs/tools/inspector for debugging

mcp call extract_content --url "https://example.com" --output_path "example.md"

mcp call scan_linked_content --url "https://example.com" | \
  mcp call create_index --content_map - --output_path "index.md"

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Distributed under the MIT License. See LICENSE for more information.

• Python 3.7+
• FastMCP (uv pip install fastmcp)
• Dependencies listed in requirements.txt