by zcaceres
Convert almost anything to Markdown. Transforms PDFs, images, web pages, DOCX, XLSX, and other formats into clean Markdo
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GitHub stars
Converts various file formats (PDFs, images, DOCX, XLSX, web pages, YouTube videos) into clean Markdown that AI assistants can read and analyze.
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.
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.
MIT
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.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
We evaluated Markdownify MCP against two servers with overlapping tools; this profile had the clearer scope statement.
I recommend Markdownify MCP for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Markdownify MCP reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Strong directory entry: Markdownify MCP surfaces stars and publisher context so we could sanity-check maintenance before adopting.
According to our notes, Markdownify MCP benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Markdownify MCP has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Markdownify MCP benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Markdownify MCP has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Useful MCP listing: Markdownify MCP is the kind of server we cite when onboarding engineers to host + tool permissions.
Markdownify MCP is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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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 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.
<a href="https://glama.ai/mcp/servers/bn5q4b0ett"><img width="380" height="200" src="https://glama.ai/mcp/servers/bn5q4b0ett/badge" alt="Markdownify Server MCP server" /></a>
pnpm install
Note: this will also install uv and related Python depdencies.
pnpm run build
pnpm start
pnpm run dev to start the TypeScript compiler in watch modesrc/server.ts to customize server behaviorsrc/tools.tsTo 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"
}
}
}
}
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
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.