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MinerU: Turn PDFs and Office Docs Into Agent-Ready Markdown
Document parsing built for agentic workflows. Extract clean structured data from messy files so your agents ingest signal, not noise.
opendatalab/MinerU ↗Most PDFs and Word docs are messy: tables break mid-page, images lose context, formatting gets scrambled. When you feed that garbage into an LLM agent, the agent hallucinates. MinerU solves this by converting PDFs, PowerPoints, and Office files into clean markdown or JSON that your agent can actually understand. It handles layout-heavy documents (financial reports, contracts, technical specs) better than generic PDF tools because it recognizes structure, preserves table relationships, and keeps image captions intact. Result: faster agent setup, fewer bad outputs, less prompt engineering to fix mangled input.
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Stop feeding your agents garbage PDFs
MinerU converts messy documents into agent-ready markdown/JSON. Built for solopreneurs and builders who ingest PDFs into workflows. Extract clean structured data from Office files, PDFs, and slide decks without the hallucinations. Worth testing if you're embedding doc processing into your stack.
Your agent eats what you feed it. If that's scrambled PDF text and broken table layouts, expect garbage outputs. MinerU converts PDFs and Office docs into clean markdown/JSON so your workflows actually work. Built for agentic builders who need signal, not noise. github.com/opendatalab/MinerU
Document processing is a bottleneck for agentic systems. MinerU addresses this directly: converts PDFs, PowerPoints, and Office files into structured markdown/JSON that LLMs can parse without hallucinating. If you're building agents that read complex documents, this cuts integration time and improves output quality. Worth evaluating for your stack.
Just integrated MinerU into a doc-processing pipeline. PDFs and Word files now land in my agents as clean markdown instead of text soup. Built by OpenDataLab, it handles the parsing work that usually eats a week of integration time. You feed it a messy document, get structured JSON or markdown back, ready for LLM consumption. Why this matters: when you're building agentic workflows, garbage input kills your chain. Clean document extraction upfront means your agent actually works with signal instead of noise. The real win is the Office format support. Most tools stop at PDFs. This handles both. Grab it here: https://github.com/opendatalab/MinerU
MinerU turns your PDF and Office doc chaos into LLM-ready markdown/JSON. No more feeding agents garbled text. Parse once, structure it right, move fast. https://github.com/opendatalab/MinerU