Marker converts PDF, DOCX, PPTX, and image files to clean Markdown, JSON, and HTML with high accuracy. It handles tables, equations, code blocks, and multi-column layouts, with optional LLM-boosted extraction for maximum fidelity.
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Added June 8, 2026
ai-agentspythongoshellfastapigitapisecurity
Works with
claude code
api
Security analysis
A92/100
mediumInstalls packages at runtime which could introduce malicious dependencies
Installs into .claude/skills of the current project.
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---
name: "Marker PDF-to-Markdown Converter"
slug: "marker-pdf-to-markdown-converter"
description: "Marker converts PDF, DOCX, PPTX, and image files to clean Markdown, JSON, and HTML with high accuracy. It handles tables, equations, code blocks, and multi-column layouts, with optional LLM-boosted extraction for maximum fidelity."
github_stars: 33237
verification: "security_reviewed"
source: "https://github.com/datalab-to/marker"
category: "Data Extraction & Transformation"
framework: "Claude Code"
tool_ecosystem:
github_repo: "datalab-to/marker"
github_stars: 33237
---
# Marker PDF-to-Markdown Converter
Marker converts PDF, DOCX, PPTX, and image files to clean Markdown, JSON, and HTML with high accuracy. It handles tables, equations, code blocks, and multi-column layouts, with optional LLM-boosted extraction for maximum fidelity.
## Installation
Use the upstream install or setup path that matches your environment:
- pip install marker-pdf
- pip install marker-pdf[full]
- pip install streamlit streamlit-ace
- pip install -U uvicorn fastapi python-multipart
Requirements and caveats from upstream:
- Commercial self-hosting requires a license — see [Commercial usage](#commercial-usage). For on-prem licensing, [contact us](https://www.datalab.to/contact?utm_source=gh-marker-onprem).
- | [Think Python](https://greenteapress.com/thinkpython/thinkpython.pdf) | Textbook | [View](https://github.com/VikParuchuri/marker/blob/master/data/examples/markdown/thinkpython/thinkpython.md) | [View](https://github...
- You'll need python 3.10+ and [PyTorch](https://pytorch.org/get-started/locally/).
Basic usage or getting-started notes:
- See [below](#benchmarks) for detailed speed and accuracy benchmarks, and instructions on how to run your own benchmarks.
- # Commercial usage
- shell
- Source: https://github.com/datalab-to/marker
- Extracted from upstream docs: https://raw.githubusercontent.com/datalab-to/marker/HEAD/README.md
## Source
- [Agent Skill Exchange](https://agentskillexchange.com/skills/marker-pdf-to-markdown-converter/)
