Mcp Markdownify Server

Markdownify MCP Server

Markdownify is a Model Context Protocol (MCP) server that converts various file types and web content to Markdown format. It provides a set of tools to transform PDFs, images, audio files, web pages, and more into easily readable and shareable Markdown text.

Features

• Convert multiple file types to Markdown:
  • PDF
  • Images
  • Audio (with transcription)
  • DOCX
  • XLSX
  • PPTX
• Convert web content to Markdown:
  • YouTube video transcripts
  • Bing search results
  • General web pages
• Retrieve existing Markdown files

Getting Started

1. Clone this repository
2. Install dependencies:

   pnpm install
   

Note: this will also install uv and related Python depdencies.

3. Build the project:

   pnpm run build
   

4. Start the server:

   pnpm start
   

Development

• Use pnpm run dev to start the TypeScript compiler in watch mode
• Modify src/server.ts to customize server behavior
• Add or modify tools in src/tools.ts

Usage with Desktop App

To integrate this server with a desktop app, add the following to your app’s server configuration:

{
  "mcpServers": {
    "markdownify": {
      "command": "node",
      "args": [
        "{ABSOLUTE PATH TO FILE HERE}/dist/index.js"
      ],
      "env": {
        // By default, the server will use the default install location of `uv`
        "UV_PATH": "/path/to/uv"
      }
    }
  }
}

Available Tools

• youtube-to-markdown: Convert YouTube videos to Markdown
• pdf-to-markdown: Convert PDF files to Markdown
• bing-search-to-markdown: Convert Bing search results to Markdown
• webpage-to-markdown: Convert web pages to Markdown
• image-to-markdown: Convert images to Markdown with metadata
• audio-to-markdown: Convert audio files to Markdown with transcription
• docx-to-markdown: Convert DOCX files to Markdown
• xlsx-to-markdown: Convert XLSX files to Markdown
• pptx-to-markdown: Convert PPTX files to Markdown
• get-markdown-file: Retrieve an existing Markdown file

Contributing

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

License

This project is licensed under the MIT License - see the LICENSE file for details.