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Mineru

Organization
Nebutra
mineru

An AI-Native skill for parsing PDF / Office / image files into clean Markdown with MinerU — a fast, zero-config document parser for AI agents. Works with NO token via the lightweight Agent API and auto-upgrades to the Standard API (token) for large files, batches, and DOCX/HTML/LaTeX export. Use when: (1) Converting PDF/Word/PPT/Excel/image to Markdown, (2) Extracting text, tables, formulas, or running OCR on scanned docs, (3) Batch-parsing a folder in parallel, (4) Piping parsed Markdown straight back to an agent or into Obsidian.

Overview

PublisherNebutra
RepositoryMinerU-Skill
Skill namemineru
Stars
132
Forks
6
Bundled files
79
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 79 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Nebutra on GitHub. Read the source before you install it.

Installation

Install the Mineru AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Nebutra/MinerU-Skill/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Nebutra/MinerU-Skill.git \
  .claude/skills/mineru
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mineru in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mineru on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mineru is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MinerU PDF Parser

Parse PDF, Office (Word/PPT/Excel), and image files into clean Markdown — with LaTeX formulas, tables, images, and OCR. One zero-dependency script, two backends, automatic routing.

Zero-config quick start (no token, no install)

bash
# Parse a local file or URL — the Agent API needs no login
python3 scripts/mineru.py paper.pdf

# Pipe the Markdown straight back to an agent
python3 scripts/mineru.py paper.pdf --stdout

# Machine-readable status for tool pipelines
python3 scripts/mineru.py paper.pdf --json

No pip install, no API key. The free Agent API handles files ≤ 10 MB / ≤ 20 pages.

Run with uv (zero-install, managed Python)

scripts/mineru.py carries PEP 723 inline metadata, so uv runs it directly — no venv, no pip install, with a uv-managed interpreter:

bash
uv run scripts/mineru.py paper.pdf --stdout       # zero-install run
uv run --no-project --with pytest pytest -q       # dev suite via uv

Power mode (token) — large files, batches, extra formats

bash
export MINERU_TOKEN="..."          # https://mineru.net/apiManage/token

# Parallel batch a directory, resume on re-run
python3 scripts/mineru.py ./pdfs/ --output ./out/ --workers 8 --resume

# Export DOCX/HTML/LaTeX alongside Markdown (auto-routes to the Standard API)
python3 scripts/mineru.py report.pdf --format docx --format latex

When a token is set, the tool auto-routes: small single files still use the free Agent API; anything large (> 10 MB / > 20 pages), batched, or needing extra export formats uses the Standard API (≤ 200 MB / ≤ 200 pages). If the Agent API hits a size/page limit, it auto-escalates to the Standard API.

Supported modalities

ModalityExtensionsOCR
PDF.pdf--ocr
Image.png .jpg .jpeg .jp2 .webp .gif .bmpbuilt-in
Word.doc .docx—
Slides.ppt .pptx—
Sheet.xls .xlsx—
HTML.html (Standard API, MinerU-HTML model)—

Common options

INPUT...          One or more files, a directory, or a URL
--output, -o      Output directory (default: ./output)
--api             auto | agent | standard   (default: auto)
--model           pipeline | vlm | MinerU-HTML  (default: vlm)
--format          docx | html | latex  (repeatable; forces Standard API)
--lang            OCR/document language (default: ch)
--ocr             Enable OCR for scanned documents
--pages           Page range, e.g. "1-10" or "2,4-6"
--workers, -w     Concurrent submit/upload/download slots (default: 8)
--resume          Skip inputs already parsed
--stdout          Print Markdown to stdout
--json            Print machine-readable status to stdout
--to SINK         Deliver into a content tool (repeatable); --list-sinks to enumerate
--obsidian PATH   Shortcut for --to obsidian with this vault
--engine          cloud | local | auto  (local/auto parse born-digital PDFs offline)
--split           Split oversized PDFs past the page caps, parse parts, merge (needs pypdf)
--chunk           Emit heading-aware RAG chunks (.chunks.json + --json)
--doctor          Environment self-check and exit

MCP server

Expose MinerU over MCP (zero-dependency stdio JSON-RPC) so an MCP host can call it:

bash
python3 scripts/mineru_mcp.py

Tools: mineru_parse, mineru_parse_to (parse + deliver to sinks), mineru_list_sinks.

Deliver into your tools (--to)

Parse once and push the Markdown into content tools via each one's official path:

bash
python3 scripts/mineru.py paper.pdf --to obsidian --to notion --to feishu

Targets: obsidian logseq siyuan notion linear yuque coda slack feishu confluence onenote ticktick dingtalk airtable wecom (all zero-dependency), plus roam and wps via optional extras. Each reads its config from env vars (run --list-sinks). Per-target auth, fidelity, and image notes: references/integrations.md.

Output

output/
└── document-name/
    ├── document-name.md    # clean Markdown
    └── images/             # extracted figures (Standard API)

Performance (real, measured)

End-to-end latency for the official demo PDF via the free Agent API: cold ≈ 14 s · warm ≈ 13 s (submit → poll → download). Batches scale with --workers. Numbers come from the no-mock live benchmark in tests/test_live.py.

Testing

bash
python3 -m pytest                      # fast unit suite (offline)
MINERU_LIVE=1 python3 -m pytest -m live -s   # real API + benchmark (no mocks)

API Reference

See references/api_reference.md. Official docs: https://mineru.net/apiManage/docs · Token: https://mineru.net/apiManage/token

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 19 more files.

Frequently asked questions

What does the Mineru AI skill do?

An AI-Native skill for parsing PDF / Office / image files into clean Markdown with MinerU — a fast, zero-config document parser for AI agents. Works with NO token via the lightweight Agent API and auto-upgrades to the Standard API (token) for large files, batches, and DOCX/HTML/LaTeX export. Use when: (1) Converting PDF/Word/PPT/Excel/image to Markdown, (2) Extracting text, tables, formulas, or running OCR on scanned docs, (3) Batch-parsing a folder in parallel, (4) Piping parsed Markdown straight back to an agent or into Obsidian.

Why use Mineru on TypingMind?

Because you install it once and use it with any model. Mineru is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mineru in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Nebutra/MinerU-Skill/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mineru?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mineru?

As many as you like. As long as a model supports skills, you can use Mineru with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mineru AI skill free?

Yes. It is published on GitHub by Nebutra under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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