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

Enables interactive chat with AI models, including document retrieval and command-based prompts via the Model Control Protocol.

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.

MCP server for Aspose PDF Cloud, enabling PDF storage, conversion, and extraction operations (merge, split, text/table/image extraction) via CLI and MCP.

A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.

A read-only MCP server for PDF analysis that enables text extraction, image extraction, metadata retrieval, and text search via natural language.

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

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.

Enables AI agents to search and query the public DOJ Epstein Files release across 20 databases, resolve EFTA numbers to official DOJ PDFs, and cross-check viral claims against a fact-checked registry.

一个基于FastMCP协议的文件向量化服务，支持自动目录监控、多格式文件处理和高效向量搜索，帮助构建个人或团队知识库。

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.

Provides tools for extracting text, performing OCR on scanned documents, and retrieving images from PDF files. It enables Model Context Protocol clients to process PDF content page-by-page through specialized extraction tools.

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.

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

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.

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

Enables generation of PDF documents from JSON specs or Markdown, supporting themes, tables, images, and other rich blocks.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.