[!TIP] MarkItDown now offers an MCP (Model Context Protocol) server for integration with LLM applications like Claude Desktop. See markitdown-mcp for more information.

[!IMPORTANT] Breaking changes between 0.0.1 to 0.1.0:

• Dependencies are now organized into optional feature-groups (further details below). Use pip install 'markitdown[all]' to have backward-compatible behavior.
• convert_stream() now requires a binary file-like object (e.g., a file opened in binary mode, or an io.BytesIO object). This is a breaking change from the previous version, where it previously also accepted text file-like objects, like io.StringIO.
• The DocumentConverter class interface has changed to read from file-like streams rather than file paths. No temporary files are created anymore. If you are the maintainer of a plugin, or custom DocumentConverter, you likely need to update your code. Otherwise, if only using the MarkItDown class or CLI (as in these examples), you should not need to change anything.

MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. To this end, it is most comparable to textract, but with a focus on preserving important document structure and content as Markdown (including: headings, lists, tables, links, etc.) While the output is often reasonably presentable and human-friendly, it is meant to be consumed by text analysis tools -- and may not be the best option for high-fidelity document conversions for human consumption.

MarkItDown currently supports the conversion from:

• PDF
• PowerPoint
• Word
• Excel
• Images (EXIF metadata and OCR)
• Audio (EXIF metadata and speech transcription)
• HTML
• Text-based formats (CSV, JSON, XML)
• ZIP files (iterates over contents)
• Youtube URLs
• EPubs
• ... and more!

Why Markdown?

Markdown is extremely close to plain text, with minimal markup or formatting, but still provides a way to represent important document structure. Mainstream LLMs, such as OpenAI's GPT-4o, natively "speak" Markdown, and often incorporate Markdown into their responses unprompted. This suggests that they have been trained on vast amounts of Markdown-formatted text, and understand it well. As a side benefit, Markdown conventions are also highly token-efficient.

Prerequisites

MarkItDown requires Python 3.10 or higher. It is recommended to use a virtual environment to avoid dependency conflicts.

With the standard Python installation, you can create and activate a virtual environment using the following commands:

bashCOPY
python -m venv .venv
source .venv/bin/activate

If using uv, you can create a virtual environment with:

bashCOPY
uv venv --python=3.12 .venv
source .venv/bin/activate
# NOTE: Be sure to use 'uv pip install' rather than just 'pip install' to install packages in this virtual environment

If you are using Anaconda, you can create a virtual environment with:

bashCOPY
conda create -n markitdown python=3.12
conda activate markitdown

Installation

To install MarkItDown, use pip: pip install 'markitdown[all]'. Alternatively, you can install it from the source:

bashCOPY
git clone git@github.com:microsoft/markitdown.git
cd markitdown
pip install -e 'packages/markitdown[all]'

Usage

Command-Line

bashCOPY
markitdown path-to-file.pdf > document.md

Or use -o to specify the output file:

bashCOPY
markitdown path-to-file.pdf -o document.md

You can also pipe content:

bashCOPY
cat path-to-file.pdf | markitdown

Optional Dependencies

MarkItDown has optional dependencies for activating various file formats. Earlier in this document, we installed all optional dependencies with the [all] option. However, you can also install them individually for more control. For example:

bashCOPY
pip install 'markitdown[pdf, docx, pptx]'

will install only the dependencies for PDF, DOCX, and PPTX files.

At the moment, the following optional dependencies are available:

• [all] Installs all optional dependencies
• [pptx] Installs dependencies for PowerPoint files
• [docx] Installs dependencies for Word files
• [xlsx] Installs dependencies for Excel files
• [xls] Installs dependencies for older Excel files
• [pdf] Installs dependencies for PDF files
• [outlook] Installs dependencies for Outlook messages
• [az-doc-intel] Installs dependencies for Azure Document Intelligence
• [audio-transcription] Installs dependencies for audio transcription of wav and mp3 files
• [youtube-transcription] Installs dependencies for fetching YouTube video transcription

Plugins

MarkItDown also supports 3rd-party plugins. Plugins are disabled by default. To list installed plugins:

bashCOPY
markitdown --list-plugins

To enable plugins use:

bashCOPY
markitdown --use-plugins path-to-file.pdf

To find available plugins, search GitHub for the hashtag #markitdown-plugin. To develop a plugin, see packages/markitdown-sample-plugin.

markitdown-ocr Plugin

The markitdown-ocr plugin adds OCR support to PDF, DOCX, PPTX, and XLSX converters, extracting text from embedded images using LLM Vision — the same llm_client / llm_model pattern that MarkItDown already uses for image descriptions. No new ML libraries or binary dependencies required.

Installation:

bashCOPY
pip install markitdown-ocr
pip install openai  # or any OpenAI-compatible client

Usage:

Pass the same llm_client and llm_model you would use for image descriptions:

pythonCOPY
from markitdown import MarkItDown
from openai import OpenAI

md = MarkItDown(
    enable_plugins=True,
    llm_client=OpenAI(),
    llm_model="gpt-4o",
)
result = md.convert("document_with_images.pdf")
print(result.text_content)

If no llm_client is provided the plugin still loads, but OCR is silently skipped and the standard built-in converter is used instead.

See packages/markitdown-ocr/README.md for detailed documentation.

Azure Document Intelligence

To use Microsoft Document Intelligence for conversion:

bashCOPY
markitdown path-to-file.pdf -o document.md -d -e "<document_intelligence_endpoint>"

More information about how to set up an Azure Document Intelligence Resource can be found here

Python API

Basic usage in Python:

pythonCOPY
from markitdown import MarkItDown

md = MarkItDown(enable_plugins=False) # Set to True to enable plugins
result = md.convert("test.xlsx")
print(result.text_content)

Document Intelligence conversion in Python:

pythonCOPY
from markitdown import MarkItDown

md = MarkItDown(docintel_endpoint="<document_intelligence_endpoint>")
result = md.convert("test.pdf")
print(result.text_content)

To use Large Language Models for image descriptions (currently only for pptx and image files), provide llm_client and llm_model:

pythonCOPY
from markitdown import MarkItDown
from openai import OpenAI

client = OpenAI()
md = MarkItDown(llm_client=client, llm_model="gpt-4o", llm_prompt="optional custom prompt")
result = md.convert("example.jpg")
print(result.text_content)

Docker

shCOPY
docker build -t markitdown:latest .
docker run --rm -i markitdown:latest < ~/your-file.pdf > output.md