"A server for finding PDF documents" matching MCP servers:

A production-ready Model Context Protocol server that bridges local document management with cloud synchronization (Notion) for AI agent integration, enabling seamless access and sync of local and cloud documents.

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.

An MCP server for PDF form filling, basic editing, and OCR text extraction. It enables users to merge, rotate, annotate, and sign PDFs, while also supporting text extraction from both searchable and scanned image-based documents.

MCP server for parsing PDF files, enabling Cursor IDE to extract text, metadata, and validate PDFs through Docker.

An MCP server that downloads PDF files from URLs and converts them to Markdown format. Supports custom file names and directories, with security measures like SSRF protection.

This server converts PDFs to markdown with intelligent academic paper detection and dual processing engines (marker-pdf for academic content, PyMuPDF for general documents), supporting URL and local file handling, page extraction, batch processing, and PDF link crawling for Claude Code analysis.

Enables AI-powered PDF manipulation through natural language commands, integrating with Claude to perform operations like merging, splitting, encrypting, optimizing, and analyzing PDFs.

Enables processing and analysis of large PDF files through text extraction, search functionality, and intelligent chunking strategies. Provides comprehensive PDF operations including metadata retrieval, page-range text extraction, and content search with contextual results.

An MCP server for local PDF inspection that classifies, searches, extracts text and tables without uploading documents or relying on OCR, surfacing reliability warnings for garbled or scanned content.

MCP server for full-text search across PDF document collections with offline indexing, ranked results, snippets, and page rendering.

A Model Context Protocol (MCP) server that provides comprehensive PDF redaction capabilities, including text and image redaction, search, and session-based in-memory operations using FastMCP and pymupdf.

Enables AI assistants to natively read, edit, and redact PDF documents in place through MCP tools, eliminating manual script execution and layout issues.

A Model Context Protocol server that lets AI clients read and process PDF files locally on your Mac without uploading them anywhere, ensuring privacy.

Extracts images from PDF files, allowing LLMs to access and analyze embedded images from local PDF 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.

Provides 18 PDF operations (merge, split, convert, edit, secure, repair, OCR) via iLoveAPI, callable from any MCP client like Claude Code or Claude Desktop.

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

An MCP server that enables AI assistants to read, search, and analyze PDF files from local paths or URLs. It provides tools for extracting specific page ranges, searching for terms, and retrieving document metadata.

An MCP server that splits PDFs by chapters/sections and reads them in Claude-friendly chunks. Enables structured reading of large PDF documents.

Provides PDF reading, text search, navigation, and form filling capabilities through MCP, with cross-platform PDF viewer integration for seamless document interaction.