22nd of 5 in Data and scraping for AI
docling
Python library and CLI that converts PDFs, Office files and more into structured text
Documentation ↗
(opens in a new tab)Website ↗
(opens in a new tab)Repository on GitHub ↗
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- Stars
- 68.8k
- License
- MIT
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Python
Checked on GitHub.
Overview
Docling parses PDF, DOCX, PPTX, XLSX, HTML, EPUB, images, audio and other formats into a unified DoclingDocument, with PDF layout, reading order, table structure, code and formula recognition. It exports to Markdown, HTML, DocLang, DocTags and lossless JSON. It runs locally via a CLI or Python API, with OCR, VLM support (GraniteDocling), an MCP server and a docling-serve API server.
Who it is for: Developers preparing documents for RAG and LLM pipelines
Strengths
- Wide input coverage: PDF, Office, ODF, EPUB, email, Apple iWork, XBRL, audio, video
- Local execution suits sensitive data and air-gapped environments
- Integrations with LangChain, LlamaIndex, Crew AI and Haystack
- Ships a CLI, Python API, MCP server and docling-serve HTTP server
Weaknesses
- Hardware requirements (RAM, GPU) are not stated in the README
- Individual models carry their own licenses, separate from the MIT codebase
- Metadata extraction and chemistry understanding are listed as coming soon
- Requires Python 3.10 or higher; 3.9 support was dropped in 2.70.0
What it needs
- GPU optional
- Docker
- Models: GraniteDocling, VLMs, OCR engines, ASR models
Head to head
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| 1 | Crawl4AIPython web crawler that converts pages to LLM-ready Markdown and JSON | 72 out of 100 |
| 3 | FirecrawlWeb scraping and crawling API that returns LLM-ready markdown | 67 out of 100 |
| #4 | paddleocrOCR and document parsing toolkit that outputs Markdown and JSON from PDFs and images | 54 out of 100 |
| #5 | Jina ReaderConverts any URL or search query into LLM-friendly markdown | 46 out of 100 |