Doc Scraper

Scrape documentation from any web URL and convert it into markdown format. Save the converted documentation to your specified output path effortlessly. Enhance your documentation management with this easy-to-use server integration.

Installation

Installing for Claude Desktop

Manual Configuration Required

This MCP server requires manual configuration. Run the command below to open your configuration file:

npx mcpbar@latest edit -c claude

This will open your configuration file where you can add the Doc Scraper MCP server manually.

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Doc Scraper MCP Server

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A Model Context Protocol (MCP) server that provides documentation scraping functionality. This server converts web-based documentation into markdown format using jina.ai's conversion service.

Features

  • Scrapes documentation from any web URL
  • Converts HTML documentation to markdown format
  • Saves the converted documentation to a specified output path
  • Integrates with the Model Context Protocol (MCP)

Installation

Installing via Smithery

To install Doc Scraper for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @askjohngeorge/mcp-doc-scraper --client claude
  1. Clone the repository:
git clone https://github.com/askjohngeorge/mcp-doc-scraper.git
cd mcp-doc-scraper
  1. Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows, use: venv\Scripts\activate
  1. Install the dependencies:
pip install -e .

Usage

The server can be run using Python:

python -m mcp_doc_scraper

Tool Description

The server provides a single tool:

  • Name: scrape_docs
  • Description: Scrape documentation from a URL and save as markdown
  • Input Parameters:
    • url: The URL of the documentation to scrape
    • output_path: The path where the markdown file should be saved

Project Structure

doc_scraper/
├── __init__.py
├── __main__.py
└── server.py

Dependencies

  • aiohttp
  • mcp
  • pydantic

Development

To set up the development environment:

  1. Install development dependencies:
pip install -r requirements.txt
  1. The server uses the Model Context Protocol. Make sure to familiarize yourself with MCP documentation.

License

MIT License

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Doc Scraper: MCP Server – MCP.Bar