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:
- 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
- Clone this repository
- Install dependencies:
pnpm install
Note: this will also install uv and related Python depdencies.
- Build the project:
pnpm run build - Start the server:
pnpm start
Development
- Use
pnpm run devto start the TypeScript compiler in watch mode - Modify
src/server.tsto 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_DIRenv 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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