タグ：ocr

Extracts text and tables from PDFs; merges, splits and rotates pages, adds watermarks, fills forms and OCRs scanned documents. The official Anthropic skill behind Claude's document features; source-available, not open source.

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.

Baidu PaddlePaddle's official OCR and document parsing tool: the paddleocr command reads text from images and parses PDFs and scans into Markdown or JSON, supporting 100+ languages with models that run locally.

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+.

Reads messy invoices and receipts (PDFs, scans, screenshots), extracts vendor, date and amount, renames and files them by vendor, category or year, keeps originals and can export a CSV for your accountant. Needs an agent with local file access; no account required.

Classic open-source OCR engine and CLI that reads text from images and outputs plain text, hOCR, searchable PDF or TSV. Supports 100+ languages; install the language data for each language you need.

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.

Free, open-source offline OCR desktop app for screenshots, batch images, scanned PDFs and QR codes, callable via the umi-ocr CLI or an HTTP API (the CLI relies on the app's local HTTP service, on by default). Windows and Linux only.

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.

Adds a searchable, copyable text layer to scanned PDFs, with automatic deskew, rotation and size optimization, outputting PDF/A by default. Built on Tesseract, supports 100+ languages and runs fully locally.

Anthropic's official small-business skill for bills: reads vendor, amount and due date from email, PDFs or photos, dedupes, codes to accounts, matches POs and drafts a payment plan. Posting and paying each need approval; it never auto-pays. Works with QuickBooks, Xero, NetSuite or file export.

Continuously records your screen and audio locally, extracting on-screen text and transcribing speech, so agents can search pages, docs and meetings you saw and summarize your day. Data stays local. Needs screenpipe running: source is free for personal use, desktop app is a subscription.

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.

Batch-translates text in manga, posters and screenshots with one command: detects text, runs OCR, erases the original and typesets the translation back into the image. Japanese-focused, with 20+ languages supported. Install from source (Python 3.10+); offline models, DeepL or LLM APIs.

Extracts subtitles burned into videos to SRT or TXT, with all OCR done locally in 87 languages. Mainly a GUI (with batch mode); the CLI backend/main.py reads the video path and subtitle area from stdin. Needs Python 3.12+ and PaddlePaddle; paths cannot contain spaces or Chinese characters.

Lightweight OCR built on PaddleOCR models converted to ONNX, recognizing Chinese and English by default on CPU alone. The rapidocr CLI reads text from screenshots, photos and scanned page images. Needs Python; downloads models on first run, then works offline. Convert PDFs to images first.

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.

Extracts issuer, amount, date, invoice number and other fields from PDF invoices using YAML/JSON templates, exporting CSV, JSON or XML. Ships several text-extraction backends, OCR for scanned invoices and an optional AI fallback.

Converts PDF, Word, PowerPoint, Excel, EPUB, web pages and images to clean Markdown locally, keeping page anchors, tables and two-column reading order, with full-text search across folders. Formerly pdf-reader-mcp; no uploads, no API key. Needs Node.js 18+; OCR for scans needs tesseract.

Describe what you need and get a typeset PDF: turn handwritten notes or scanned textbooks into LaTeX handouts and cheat sheets, make exams with answer keys, write papers, theses, posters, resumes and letters. 27 templates plus chart and mail-merge scripts. Needs TeX Live (install script included).

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.

Turns web pages, long PDFs, Word files, images or code into tutor-style study notes: Markdown notes plus searchable HTML knowledge cards with concept breakdowns and mind maps. Needs Python 3.8+, plus Chrome for some sites; the optional tutor chat needs an OpenAI-compatible API key.

Connects to self-hosted or managed Nextcloud so agents can manage files, calendars, contacts, notes, Deck boards and mail, and read PDF and Word content (OCR for scans is opt-in); suits teams that value data ownership. Needs a Nextcloud account with an app password, and uv.