PDF Reader
Accelerate PDF document processing for AI agents by extracting text, images, and metadata with parallel execution and precise content ordering.
About
PDF Reader is a production-ready Model Context Protocol (MCP) server designed to provide AI agents with high-performance PDF processing capabilities. It addresses the limitations of traditional sequential PDF processing by offering 5-10x faster parallel execution, Y-coordinate based content ordering for natural reading flow, and robust error resilience. Built with TypeScript and boasting over 94% test coverage, this tool ensures reliable extraction of text, images, and metadata from both local files and URLs, making it an essential component for any AI agent requiring efficient and accurate PDF comprehension.
Key Features
- 5-10x faster parallel processing for rapid document parsing
- Y-coordinate based content ordering to preserve natural reading flow for AI models
- Production-ready reliability with 94%+ test coverage, strict TypeScript, and per-page error resilience
- Robust extraction of full text, base64-encoded images with metadata, and PDF metadata
- Flexible path support for absolute and relative file paths (Windows/Unix) and URL sources
- 310 GitHub stars
Use Cases
- Automating document analysis and information extraction from reports, manuals, and contracts.
- Efficiently batch processing multiple PDF files concurrently from various sources for indexing or migration.
- Enhancing AI agent comprehension by enabling fast and accurate parsing of PDF documents.
