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A dev-time MCP server that lets coding agents read documentation directly from installed @particle-academy/\* packages, ensuring version-matched docs without network calls.

Provides AI assistants like Claude or Cursor with access to Payman AI's documentation, helping developers build integrations more efficiently.

An MCP server that translates scientific PDF documents while preserving original formulas, charts, and layout. It utilizes an OpenAI-compatible backend to provide tools for document translation and language listing.

Enables AI agents to efficiently process large local and online PDFs through selective extraction of text, images, and metadata. It provides tools for content search and document outline navigation to optimize context window usage.

A local document processing toolkit for AI agents that extracts text, converts PDFs to Markdown, merges files, extracts tables, and summarizes documents without external API dependencies.

An MCP server that enables interaction with the PDF Generator API for automated document generation and management. It supports both stdio and HTTP transports, allowing AI models to create and handle PDFs using OpenAPI v4 specifications.

Turn markdown into designed PDFs with cover page, table of contents, and code blocks that hold across pages. One command from Claude Desktop, Claude Code, Cursor, Cline, Zed, or any MCP-capable client.

An MCP server that provides tools for reading, writing, and manipulating PDF files, including text extraction, metadata retrieval, and merging or splitting documents. It also enables users to create PDFs from plain text and convert specific pages or entire documents into images.

Enables LLMs to read and extract content from PDF files with high-fidelity LaTeX recognition and layout awareness using a Python-based extraction engine. It includes a robust Node.js fallback and supports page range filtering for efficient processing of large documents.

PDF Merge AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

PDF extraction that actually works. The only extractor that audits every page. #2 on opendataloader-bench. 5 MCP tools for AI agents: metadata, convert, analyze, batch, structured extraction.

A MCP server that supports AI assistants to read and analyze PDF files, providing functions such as PDF metadata extraction, page range reading, and keyword search

Empowers AI agents to securely read and extract information (text, metadata, page count) from PDF files within project contexts using a flexible MCP tool.

Enables reading and extracting content from PDF documents including text (as Markdown), images, tables, and metadata from both local files and URLs, with OCR support for scanned documents.

Enables reading and extracting text content from PDF files, supporting both local file system access and remote PDF URLs with automatic encoding detection.

Enables reading, searching, and metadata extraction from PDF files without loading the entire content into the context window. It provides efficient tools for text cleaning, page-specific extraction, and context-aware search results.

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.

Enables AI agents to securely read and extract information from PDF files including text content, metadata, and page counts from both local files and URLs within the project context.

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.

Provides random access to PDF contents with selective page extraction, text search, outline navigation, image extraction, and page rendering capabilities. Reduces token usage by allowing targeted content extraction instead of processing entire documents.