NameetP/pdfmux

Overview

PDF extraction tool that verifies its own output for reading order accuracy. Uses a rule-based approach with no AI or GPU, achieving high accuracy at zero cost.

Best for

Best for
Developers needing lightweight, verifiable PDF text extraction without AI costs

Use cases

• Extracting text from PDFs while preserving logical reading order
• Building reliable document processing pipelines without AI dependencies
• Validating extraction quality automatically for downstream tasks

How to use

Install

pip install pdfmux

Tools exposed

• GPT-4o

Tested with

Claude Desktop, Claude Code, Cursor, Continue, ChatGPT

Notes

PDF extraction tool that verifies its own output for reading order accuracy. Uses a rule-based approach with no AI or GPU, achieving high accuracy at zero cost.

66 stars on GitHub. Last updated 2026-05-22. Licensed MIT.

Use cases

• Extracting text from PDFs while preserving logical reading order
• Building reliable document processing pipelines without AI dependencies
• Validating extraction quality automatically for downstream tasks

Pros

• No AI or GPU required, runs on any machine
• Self-checking mechanism ensures output accuracy
• Free and open source with a simple Python interface

Cons

• Limited to reading order extraction, no layout or table parsing
• Small community and limited documentation due to low star count
• May struggle with complex PDF layouts or scanned documents

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.