Markdownify MCP

Markdownify MCP

zcaceres

Converts various file formats (PDFs, images, DOCX, XLSX, web pages, YouTube videos) into clean Markdown that AI assistants can read and analyze.

Convert almost anything to Markdown. Transforms PDFs, images, web pages, DOCX, XLSX, and other formats into clean Markdown that AI assistants can read and analyze. 2,400+ GitHub stars.

2,43892 views200Local (stdio)

What it does

  • Convert PDFs to Markdown
  • Transform images to readable text
  • Extract YouTube video transcripts
  • Convert Office documents (DOCX, XLSX, PPTX)
  • Turn web pages into Markdown
  • Transcribe audio files to text

Best for

Content creators processing diverse file formatsResearchers analyzing documents with AI assistantsDevelopers building document processing workflows
2,400+ GitHub starsSupports 6+ file formatsYouTube transcript extraction

About Markdownify MCP

Markdownify MCP is a community-built MCP server published by zcaceres that provides AI assistants with tools and capabilities via the Model Context Protocol. Convert almost anything to Markdown. Transforms PDFs, images, web pages, DOCX, XLSX, and other formats into clean Markdo It is categorized under productivity, developer tools.

How to install

You can install Markdownify MCP in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

Markdownify MCP is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

Markdownify MCP Server

Help! I need someone with a Windows computer to help me add support for Markdownify-MCP on Windows. PRs exist but I cannot test them. Post here if interested.

markdownify mcp logo

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.

Markdownify Server MCP server

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.

  1. Build the project:
    pnpm run build
    
  2. 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. File extension must end with: *.md, *.markdown.

    OPTIONAL: set MD_SHARE_DIR env var to restrict the directory from which files can be retrieved, e.g. MD_SHARE_DIR=[SOME_PATH] pnpm run start

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.

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