pdf-rescue-mcp
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- AlicenseNot gradedqualityDmaintenanceProvides intelligent OCR and PDF processing capabilities that automatically detect whether PDFs contain digital text or scanned images and apply appropriate extraction methods. Supports text extraction, OCR processing, structure analysis, and batch operations.MIT
- FlicenseNot gradedqualityDmaintenanceProvides OCR capabilities to extract text from PDF documents using Tesseract, with support for multiple languages including English and Simplified Chinese.3-
- AlicenseNot gradedqualityDmaintenanceEnables comprehensive PDF processing including text extraction, image extraction, and OCR capabilities for reading text within images across multiple languages.12MIT
- AlicenseAqualityBmaintenanceEnables AI agents to convert images and PDFs, including large scanned books, into Markdown through GLM-OCR, with support for long-image slicing, progress tracking, and asynchronous OCR tasks.71MIT
- AlicenseNot gradedqualityBmaintenanceProvides OCR capabilities to add searchable text layers to scanned PDFs, with tools to check OCR need, process single files or batch folders, and integrate with Zotero attachment storage.MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI-powered extraction and analysis of PDF documents with 40+ specialized tools for text, tables, images, layout analysis, security assessment, and document intelligence. Supports both text-based and scanned PDFs with OCR capabilities.797 PyPI10MIT
TDQS
Scored across 26 tools
Several tools have overlapping functions: rescue_pdf serves as a catch-all that duplicates diagnosis, planning, extraction, and monitoring; extract_book_text and extract_book_background are nearly identical; diagnose_pdf, inspect_pdf_text_layer, and plan_pdf_job all analyze PDFs with different angles. Agents will likely misselect among these.
All 26 tools use a consistent snake_case verb_noun pattern (e.g., get_job_status, cancel_job, start_ocr_capacity_profile), which is highly predictable and easy to follow.
26 tools is above the 25 threshold, and the count feels inflated by redundant tools like extract_book_text/extract_book_background and four separate OCR capacity profiling tools. The core purpose could be served with fewer, better-differentiated tools.
The tool set covers the full lifecycle of PDF diagnosis, extraction, monitoring, recovery, quality auditing, and history sharing, which is thorough. Minor gaps exist, such as no way to delete glossary entries or repair corrupted PDFs directly, but these are workaroundable.