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MinerU
Open-source AI document parser that converts PDFs, images, and documents into structured Markdown or JSON for AI workflows.
FreeStarting price
324KMonthly visits
42Popularity
About MinerU
MinerU is an open-source AI-powered document parsing platform designed to convert unstructured documents such as PDFs, images, and office files into structured, machine-readable formats like Markdown, JSON, and LaTeX. It intelligently extracts content including headings, paragraphs, tables, formulas, images, and metadata while preserving the original document’s layout, hierarchy, and semantic meaning. The tool is particularly suited for developers, data scientists, researchers, and engineers building AI pipelines, RAG systems, knowledge bases, and automation workflows where clean, structured input data is critical. MinerU supports batch processing and offers flexible integration options via API, CLI, or local deployment, enabling efficient handling of large-scale documents. Its structure-aware parsing and multilingual OCR capabilities make it versatile for diverse document types and languages, ensuring high accuracy and usability across different workflows. Additionally, MinerU provides native support for mainstream Agent frameworks and the MCP protocol, allowing for seamless integration into existing AI workflows and automation processes. The platform also excels in parsing complex elements such as rotated tables, merged cells, and mathematical formulas, outputting them in machine-readable formats like CSV, HTML, or Markdown to facilitate downstream applications.
Key features
- Converts PDFs, images, and documents into structured Markdown or JSON
- Extracts tables, formulas, images, and metadata with high accuracy
- Preserves document layout, hierarchy, and reading order
- Supports batch processing and scalable architecture for large documents
- Enables integration via API, CLI, or local deployment
- Provides multilingual OCR support for diverse document types
- Maintains semantic meaning during extraction
- Facilitates RAG pipelines and AI workflows with clean structured data
Use cases
- Building RAG systems from PDFs and knowledge documents
- Preparing datasets for machine learning and AI training
- Extracting tables and structured data for analytics workflows
Pros
- Open-source platform with community-driven development and support
- Supports a wide range of document formats including PDF, Word, PPT, Excel, images, and web URLs
- Highly structured output in Markdown, JSON, or LaTeX while preserving document hierarchy and layout
- Native integration with popular Agent frameworks and MCP protocol for seamless workflow adoption
- Multilingual OCR and advanced parsing for complex elements like tables, formulas, and chemical structures
Cons
- Requires technical expertise for local deployment and customization
- Performance may vary with highly complex or poorly formatted documents
- Limited built-in support for proprietary or niche document formats
Frequently asked questions about MinerU
What types of documents can MinerU parse?
MinerU supports parsing a wide range of document formats including PDF, Word, PowerPoint, Excel, images, and web URLs. It is designed to handle complex layouts and structures commonly found in these formats.
Who is MinerU designed for?
MinerU is designed for developers, data scientists, researchers, and engineers who need to process and extract structured data from unstructured documents for AI pipelines, RAG systems, knowledge bases, or automation workflows.
How does MinerU integrate with Agent frameworks?
MinerU natively supports mainstream Agent frameworks and the MCP protocol, enabling seamless integration into existing AI workflows. It provides dedicated channels for Agent automation and can export data to platforms like Dify or Notion.
Can MinerU handle complex elements like tables and formulas?
Yes, MinerU excels at parsing complex elements such as tables with rotated layouts, merged cells, and formulas. It outputs tables in structured formats like CSV, HTML, or Markdown and converts formulas into LaTeX or MathML for machine readability.
Is MinerU suitable for multilingual documents?
Yes, MinerU includes multilingual OCR capabilities, making it suitable for processing documents in various languages while preserving structure and context.
How can I get started with MinerU?
You can get started with MinerU by downloading the client, using the online demo, or integrating it via API or CLI. The platform offers documentation and guides for local deployment and integration with Agent frameworks.
MinerU traffic & engagement
mineru.net · third-party estimates from Similarweb
Data as of Sep 2026Full AI website ranking →
Monthly visits · Sep 2026324K-17.4% MoM12-month high 534K (Jun 2026)
Rank among AI websites#999▼ 102 vs last monthof 8,652 tools on aitoolnavio™
Top marketChina81.7%Top 5 countries bring 96% of visits
Average visit4mLonger than 89% of AI sites
Pages per visit4.53More than 89% of AI sites
Bounce rate30%Lower than 94% of AI sites
Similarweb global rank#117,183#4,457 in China
Traffic trend
Last 4 months · grows by one month every month
- Jun 2026534K
- Jul 2026370K−30.7%
- Aug 2026392K+6%
- Sep 2026324K−17.4%
Where visitors come from
Share of visits by channel
No measurable traffic from Paid Referrals or Mail.
Top countries
Share of visits · estimated visits
Other countries: 3.8%
Visits sent by AI assistants
How people reach this site from other AI tools
98 a month
Compared with similar tools
Coding & Development · Sep 2026
Traffic figures are third-party estimates, good for scale and trends; they can differ from a company's own numbers. Updated monthly.
