"Information or resources related to PDF files" matching MCP servers:

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Enables read-only listing and reading of files in an Azure Files SMB share, enforcing each user's NTFS permissions per request.

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

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.

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.

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。

Enables AI-powered extraction and analysis of PDF documents with 40+ specialized tools for text, tables, images, layout analysis, security assessment, and document intelligence. Supports both text-based and scanned PDFs with OCR capabilities.

MCP server for extracting text from PDF files, supporting local files and URLs.

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.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

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

An MCP server that extracts energy-usage charts from utility-bill PDFs, returning structured time-series data and annotated images.

MCP server for generating professional PDFs from structured JSON in AI agents like Claude or Cursor, using pure Node.js with embedded fonts and precision text layout.

Enables AI agents to permanently remove personally identifiable information from PDF documents, returning redacted files with the sensitive text deleted rather than merely covered. Supports scanned documents, multiple languages, entity types, and optional human review.

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.

A comprehensive tool server for reading, merging, and extracting content from PDF files via local paths or direct URLs. It enables metadata retrieval, regex searching, and page-specific text extraction with built-in caching and workspace-restricted security.

Enables AI agents to process and inspect PDFs by detecting document type, extracting text, and generating Markdown with layout information.

Enables AI models to perform file operations, user management, automations, and more within Files.com's secure file transfer platform via the Model Context Protocol.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.