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

Upload, edit, compress, protect, redact, and compare PDFs with KDAN PDF in Claude and ChatGPT.

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.

Full-text search and retrieval over official congressional documents (hearings, committee reports, Congressional Record) with citations and govinfo.gov links, designed for grounding AI answers in the official record.

Let your AI assistant create professional Office documents — PowerPoint, Word, Excel, emails & XML — with a single prompt.

Enables AI assistants to query PDF documents by ingesting them into a vector database and generating answers grounded in the actual documents.

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.

Safely downloads and extracts public tender documents from PDFs, Office files, and ZIP archives into text with structured signals, while also supporting document comparison and base64 extraction.

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.

Enables uploading, arranging, merging, and downloading PDFs through an MCP-compatible LLM client by interacting with a PDF Merger API.

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.

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

Enables creative PDF generation with full design control including colors, shapes, emoji, and Unicode support. Supports everything from simple documents to artistic masterpieces using PDFKit's powerful API.

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.

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.

This MCP server enables AI agents to view PDFs as accessible HTML with bounding-box citations, and provides tools for layout-aware parsing, schema extraction, cross-document Q&A, and PDF rendering.

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

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

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

An MCP server that enables users to read, search, and analyze PDF documents. It provides tools for extracting text, viewing metadata, searching content with context, and generating word statistics.