Herramientas

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+.

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.

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.

Generates natively editable PPTX from PDFs, Word files, web pages and other sources, with native shapes, data charts and master layouts. Can also fill your own template and add animations and narration to finished decks. Needs Python 3.10+ and its dependencies.

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.

Rendering engine that lays out HTML and CSS and exports PDF, supporting paged media and other print style standards, ideal for generating reports, invoices and receipts in bulk. Written in Python; depends on the system Pango library.

Open-source PDF table extraction with a camelot CLI: exports tables from financial reports, bank statements and statistical reports to Excel, CSV or Markdown, with an accuracy score. Needs Python 3.10+; handles text-based PDFs by default, scans need the ml and ocr extras. Double-check results.

Converts PDFs to editable Word files, keeping paragraphs, tables, images and layout as closely as possible, and can extract tables alone, handy when a contract or exam only exists as PDF. Needs Python; digital PDFs only, OCR scans first. No longer actively maintained by Artifex.

Recognizes images or whole PDFs (including scans) with math formulas and tables into Markdown and LaTeX, strong on English and Chinese and supporting 80+ languages, handy for digitizing exams, lecture notes and study notes. An open-source Mathpix alternative that runs locally with Python.

The Docling project's official MCP: converts PDF, Word, PowerPoint and more into structured documents with layout and table detection and OCR for scans, and lets agents build new documents paragraph by paragraph and export Markdown. Local mode needs Python and uv, or use your own Docling Serve.

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.