Enterprise DNA
M MCP Servers Developer low

microsoft/markitdown

by Various

Python tool for converting files and office documents to Markdown.

M

MCP

microsoft/markitdown

Added 1 June 2026

#autogen #autogen-extension #langchain #markdown #microsoft-office #openai #pdf

Overview

Python tool that converts files and Office documents into Markdown format. Handles multiple input types including PDFs, Word docs, Excel sheets, and images, outputting clean Markdown suitable for further processing or storage.

Best for

Best for
Developers building document pipeline tools or migrating content to Markdown-based systems

Use cases

  • Converting legacy Word documents to Markdown for documentation systems
  • Batch processing spreadsheets into structured Markdown tables
  • Extracting text from PDFs while preserving basic formatting

How to use

Install

pip install -e 'packages/markitdown[all]'

Tools exposed

  • Capability
  • Cost

Tested with

ChatGPT

Notes

Python tool that converts files and Office documents into Markdown format. Handles multiple input types including PDFs, Word docs, Excel sheets, and images, outputting clean Markdown suitable for further processing or storage.

138,078 stars on GitHub. Last updated 2026-05-26. Licensed MIT.

Use cases

  • Converting legacy Word documents to Markdown for documentation systems
  • Batch processing spreadsheets into structured Markdown tables
  • Extracting text from PDFs while preserving basic formatting

Pros

  • Supports diverse file formats including Office suite documents
  • High community adoption with 138k+ GitHub stars
  • Handles images and extracts text from visual content

Cons

  • Python-only, requires runtime environment setup
  • Conversion quality varies by source format complexity
  • Limited control over output formatting rules

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Supports diverse file formats including Office suite documents
  • High community adoption with 138k+ GitHub stars
  • Handles images and extracts text from visual content

Cons

  • Python-only, requires runtime environment setup
  • Conversion quality varies by source format complexity
  • Limited control over output formatting rules

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