A local MCP server that drives PDFium and pypdf to perform comprehensive PDF operations including inspection, assembly, page editing, watermarking, rendering, extraction, form filling, encryption, compression, attachments, bookmarks, and metadata management.
Enables comprehensive PDF analysis and manipulation including page size analysis, chapter extraction, splitting, compression, merging, and conversion to images. Provides both MCP server interface for AI assistants and Streamlit web interface for direct user interaction.
A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.
An MCP server for reading, rendering, and searching PDF files, specifically optimized for LLMs to extract text, tables, and technical diagrams. It enables metadata retrieval, multi-format text extraction, and page-to-image rendering using PyMuPDF.
MCP server that reads PDFs and exposes them as structured Markdown, metadata, outlines, images, and tables to LLM consumers via tools like pdf_read_markdown and pdf_info.
