OCR Document Intelligence
Enables AI assistants to intelligently read and process both scanned and digital PDF documents using integrated Optical Character Recognition (OCR) and a robust caching system.
About
This proof-of-concept details the development of a custom server designed to enhance AI assistants like Claude Desktop with advanced document processing capabilities. It chronicles a real-world journey, from navigating complex setup challenges with Anthropic's Model Context Protocol (MCP) to integrating OCR for scanned PDFs. The system intelligently determines whether a PDF requires OCR, extracting text from both standard and image-based documents. It features an efficient caching mechanism for rapid subsequent access, robust security measures including path validation and file type restrictions, and a modular design for easy expansion of capabilities, empowering AI to interact seamlessly with complex paperwork.
Key Features
- Tools for listing available documents and performing full-text content search
- Intelligent PDF text extraction with automatic OCR fallback for scanned documents
- Modular architecture enabling easy integration of new tools and capabilities
- High-performance caching system for OCR results, drastically reducing processing time
- 0 GitHub stars
- Secure file access with path validation and file type restrictions
Use Cases
- Summarizing and analyzing complex legal documents like HOA covenants or leases using an AI assistant.
- Extracting key information and data from scanned reports, invoices, or other image-based PDFs.
- Enabling AI assistants to answer specific questions about personal or business documents instantly.
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