Инструменты

From Microsoft: converts PDF, Word, Excel, PowerPoint, HTML and other files or URLs to Markdown so agents can read and search them. A single convert_to_markdown tool over STDIO or local HTTP.

Converts PDF, Word, Excel, PowerPoint, HTML, images, audio and more into Markdown that keeps headings, lists and tables, ready for LLMs to read and analyze. Maintained by Microsoft; requires Python 3.10+.

OCRs photos of visa documents such as bank, employment or income certificates, translates them into English and builds a side-by-side bilingual PDF. Needs Python (pillow, reportlab) and an OCR engine. Not an official certified translation: verify names, amounts and dates.

Official PaddleOCR MCP: text recognition and layout parsing for images and PDFs (PP-OCR, PP-StructureV3, PaddleOCR-VL), returning text or Markdown. Runs inference locally, or calls the official API or a self-hosted service.

Document parser from OpenDataLab that turns PDFs, images and Office files into Markdown or JSON, handling tables, formulas and complex layouts well, with page-by-page reading and citation anchors for agents. Parses locally by default; needs Python 3.10+.

Parses PDF, DOCX, PPTX, XLSX, HTML, images and audio, recovering layout, reading order, tables and formulas, and exports Markdown, HTML or lossless JSON. Started by IBM Research, now hosted by the LF AI & Data Foundation; runs fully locally.

Command-line toolkit for transcoding, cutting, joining, frame extraction and streaming of audio and video, including ffmpeg, ffprobe and ffplay. A core dependency for agents handling media. The GitHub repo is the official mirror.

Converts PDFs, images, PPTX, DOCX, XLSX, EPUB and more into Markdown, JSON or HTML, preserving tables, formulas and layout, with optional LLM help for higher accuracy. Needs Python 3.10+ and PyTorch; large-scale commercial use of the model weights needs a paid license.

AI2's tool for converting PDFs and scans to Markdown with a vision LLM, handling equations, tables, handwriting and multi-column layouts, suited to bulk digitizing papers and archives. Local runs need an NVIDIA GPU with 12GB+ VRAM; otherwise use a paid OpenAI-compatible remote endpoint.

Open-source Simplified/Traditional Chinese converter: deterministic dictionary-based conversion (no LLM) covering variant characters and regional vocabulary for mainland China, Taiwan and Hong Kong, with limited Japanese kanji support. Runs offline; CLI plus Node.js and Python APIs.

Uses LLMs to translate EPUB, TXT, Markdown, SRT, PDF and other files into side-by-side bilingual editions, via OpenAI, Anthropic, Gemini and other APIs or DeepL and Google Translate. LLM APIs need your own key or a Codex subscription. Only translate content you have rights to.

Converts and two-way syncs Jupyter notebooks with plain Python scripts or Markdown, so agents can edit research and teaching notebooks like ordinary text and diffs stay readable. Needs a local Python environment; install with pip.

Translates entire books: splits PDF, DOCX or EPUB into chunks for parallel subagents, keeps terminology consistent, resumes interrupted runs and verifies with hashes, then outputs HTML, DOCX, EPUB or PDF. Needs Calibre, Pandoc and Python.

Open-source toolkit widely used in localization: converts between PO, XLIFF, TMX, CSV, subtitle and other translation formats, counts words, runs 40+ translation checks with pofilter and extracts frequent terms with poterminology. Needs Python 3.11+.

MinerU's official MCP: parses PDF, Word, PowerPoint and images into Markdown via the mineru.net cloud API, keeping tables and formulas. The keyless Flash mode works out of the box; add a token for higher quotas and more formats.