MarkItDown: Microsoft's Tool for Converting Almost Anything to Markdown Microsoft has released MarkItDown, a lightweight Python library and CLI tool that converts PDFs, Word documents, Excel sheets, PowerPoint decks, and other file formats into Markdown for use in LLM pipelines. The tool preserves structural elements like headings, tables, lists, and links while producing token-efficient output that large language models can process natively. MarkItDown supports optional features including LLM-powered image description generation, OCR for scanned documents, and integration with Azure Document Intelligence for enterprise-grade parsing. If you've been building LLM-powered applications, you've likely run into the same problem: your data lives in PDFs, Word documents, Excel sheets, and PowerPoint decks — but your AI pipeline expects clean text. Copy-pasting doesn't scale, and most conversion tools either strip too much structure or produce noisy output. Microsoft's MarkItDown is built specifically for this gap. It's a lightweight Python utility that converts a wide range of file formats into Markdown, preserving the structure that matters: headings, tables, lists, and links. MarkItDown is a Python library and CLI tool that converts files and documents into Markdown. It is not designed for pixel-perfect human-readable output. The explicit goal is to feed text into LLMs and text analysis pipelines — and Markdown is the right format for that because most large language models understand it natively and it is highly token-efficient. Supported formats include: That's a broad surface area for one library. You need Python 3.10 or higher. The simplest way to get everything: pip install 'markitdown all ' The all flag installs all optional dependencies for every supported format. If you want a leaner install, you can pick specific formats: pip install 'markitdown pdf,docx,pptx ' Available optional extras: pdf , docx , pptx , xlsx , xls , outlook , audio-transcription , youtube-transcription , az-doc-intel . It is recommended to work inside a virtual environment: python -m venv .venv source .venv/bin/activate pip install 'markitdown all ' The command-line interface is straightforward: Convert a file and print to stdout markitdown report.pdf Save output to a file markitdown report.pdf -o report.md Pipe input cat report.pdf | markitdown That's it. No configuration required for basic use. For programmatic use in your pipeline: python from markitdown import MarkItDown md = MarkItDown enable plugins=False result = md.convert "financials.xlsx" print result.text content The result.text content attribute holds the converted Markdown string. python from markitdown import MarkItDown md = MarkItDown Word document result = md.convert "proposal.docx" PowerPoint deck result = md.convert "slides.pptx" CSV file result = md.convert "data.csv" HTML file result = md.convert "page.html" print result.text content The API is consistent regardless of file type. You call .convert and get back a result object. If you pass an image file or a PowerPoint with images , MarkItDown can call an LLM to generate descriptions for those images, which then become part of the Markdown output. You supply your own client: python from markitdown import MarkItDown from openai import OpenAI client = OpenAI md = MarkItDown llm client=client, llm model="gpt-4o" result = md.convert "diagram.jpg" print result.text content This is useful when the actual visual content of an image matters for downstream processing, not just the file metadata. For PDFs and Office documents that contain images with embedded text scanned documents, screenshots inside slides , MarkItDown supports a separate OCR plugin: pip install markitdown-ocr pip install openai python from markitdown import MarkItDown from openai import OpenAI md = MarkItDown enable plugins=True, llm client=OpenAI , llm model="gpt-4o", result = md.convert "scanned report.pdf" print result.text content The OCR plugin uses the same LLM vision pattern as image descriptions — no separate ML libraries or binaries are required. For enterprise-grade document parsing better table extraction, form recognition , MarkItDown integrates with Azure Document Intelligence: CLI markitdown report.pdf -o report.md -d -e "