"A tool for reading and converting PDF files" matching MCP servers:

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

A 4-stage reading companion that helps users set reading goals, discover books, track progress, and deepen learning through reflection, integrated with Claude Desktop.

Enables local EPUB reading with AI agents, supporting annotations, parallel editions, and MCP tools.

A local stdio MCP server for managing files on XServer via SFTP, enabling secure file operations, backups, and workspace management for XServer hosting.

A local MCP server for low-token co-reading: import a book, split it into chapter-sized chunks, read it chunk by chunk, and keep notes so a session can resume without re-reading the whole book.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

A Model Context Protocol server that enables AI agents to read, search, and extract content from PDF files.

Full-stack PDF intelligence MCP server for extracting, manipulating, annotating, converting, validating, and RAG-searching PDFs through a unified tool surface and React workbench.

A lightweight MCP server for basic file operations, enabling reading, writing, and listing files securely via the Model Context Protocol.

A local MCP server that gives Claude a durable reading room for EPUB and plain text books, enabling chunk-by-chunk navigation, annotations, progress tracking, and shared margin cards.

Enables a shared reading room where users and Claude can import EPUB or text books, read chunk-by-chunk, annotate passages, search, track progress, and resume from unread sections.

A Model Context Protocol server that provides a scratchpad tool for LLMs to organize thoughts, take notes, and plan approaches to complex problems.

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.

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.

Enables PDF processing and analysis including text extraction, metadata retrieval, search, page manipulation, splitting/merging, conversion to images, and form handling.

A PDF MCP server for extracting text, rendered pages, tables, links, annotations, outlines, metadata, and text statistics from PDF files.

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.

Converts Markdown files to Word (.docx) and PDF documents. Supports .dotx templates for branded styling and batch conversion.

Memory-efficient MCP server for reading and splitting large PDF files page by page using PyMuPDF.

Enables AI agents to read and analyze PDF documents for natural language Q\&A. Supports multiple LLM providers including Google Gemini, Anthropic Claude, and OpenAI.