A Model Context Protocol server that extracts and processes content from PDF documents, providing text extraction, metadata retrieval, page-level processing, and PDF validation capabilities.
Empowers AI agents to securely read and extract information (text, metadata, page count) from PDF files within project contexts using a flexible MCP tool.
An MCP server that provides comprehensive PDF processing capabilities including text extraction, image extraction, table detection, annotation extraction, metadata retrieval, page rendering, and document structure analysis.
A server that provides tools for reading and processing PDF documents, allowing users to list available PDFs and extract their content in Markdown format.
A PDF processing server that extracts text via normal parsing or OCR, and retrieves images from PDF files through the MCP protocol with a built-in web debugger.
An MCP server that provides a tool to extract text content from local PDF files, supporting both standard PDF reading and OCR capabilities with optional page selection.
A Model Context Protocol (MCP) based server that efficiently manages PDF files, allowing AI coding tools like Cursor to read, summarize, and extract information from PDF datasheets to assist embedded development work.
A Model Context Protocol server that connects MCP-compatible clients like Claude and VS Code to your Readwise Reader library, allowing them to list, retrieve, and update documents in your personal knowledge repository.
Enables Claude to interact with the Readwise Reader API, allowing for saving, listing, updating, and deleting documents with complete metadata and content access through natural language.
mcp using PyPDF2 to:
• merge-pdfs
• extract-pages
• search-pdfs
• merge-pdfs-ordered (merge in user spec. order)
• find-related-pdfs (regex extracted text for related PDF files)
A server providing PDF form manipulation tools via MCP's API, allowing users to find PDFs across directories, extract form field information, and visualize form fields in documents.
A Model Context Protocol server that enables Claude to fetch, process, and extract information from PDF documents, including LaTeX mathematical equations.
Provides PDF.co API functionality through the Model Context Protocol, enabling AI assistants to perform various PDF processing tasks like conversion, editing, searching, and security operations.
A multi-server system that converts PDF documents to Markdown format using FastMCP architecture with upload and convert servers orchestrated by a reactive client agent.
A Model Context Protocol server that enables intelligent document search and retrieval from PDF collections, providing semantic search capabilities powered by OpenAI embeddings and ChromaDB vector storage.
A lightweight MCP server that provides read-only access to SQLite databases, allowing users to execute SELECT queries, list tables, and describe table schemas.
Provides efficient handling of large Excel files through automatic chunking and pagination, using MCP to enable seamless file reading and management features such as sheet selection and error handling.
A Model Context Protocol (MCP) server that allows AI models to safely access and interact with local file systems, enabling reading file contents, listing directories, and retrieving file metadata.
An MCP server that converts Excel and Apple Numbers files to PDF format, enabling AI assistants like Claude to perform file conversion directly through conversation.
Provides tools for AI assistants to explore and interact with MariaDB databases, allowing them to list databases, view tables, inspect schema definitions, and query data.
Converts Markdown to styled PDFs using VS Code's markdown styling and Python's ReportLab, providing a simple note storage system with custom URI scheme.
A document knowledge base system that enables users to upload PDFs and query them semantically through a web interface or via the Model Context Protocol, allowing integration with AI tools like Cursor.