"PDF" matching MCP servers:

Local Markdown-to-PDF MCP server with four tools to list themes, render a document, validate an existing PDF, and create a document from a template. Requires Python, Pango/GLib, and fonts; its 0–100 report is heuristic, not print or accessibility certification.

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.

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 agents to search local component-manual corpora via hybrid semantic, full-text, and substring retrieval with table recognition and OCR fallback for scanned pages. Provides tools for literal/regex grepping, reading single or multiple pages, navigating bookmarks and outlines, listing categories and indexed files, and checking index and dependency status.

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

Enables MCP clients to extract tables and text from digital PDF invoices, bank statements, and bills into CSV, JSON, or Excel, with automatic PII redaction by default.

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 for PDF utilities including text extraction, metadata, merge/split/rotate, and PDF-to-image conversion.

A Model Context Protocol (MCP) based server that efficiently manages PDF files, allowing AI coding tools like Cursor to read, summarize, and extract information from PDF datasheets to assist embedded development work.

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

pdf-tools-mcp

MCP server for rendering Mermaid diagrams to SVG and converting Markdown with callout blocks into styled PDF reports.

A high-performance Model Context Protocol server that enables AI agents to extract text, images, and metadata from PDF documents using parallel processing. It features intelligent Y-coordinate content ordering to preserve natural reading flow and supports both local files and URL-based sources.

Enables AI agents to parse and extract text, metadata, and statistics from PDF documents via URL, with x402 micropayments on Base Mainnet.

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

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 server providing PDF form manipulation tools via MCP's API, allowing users to find PDFs across directories, extract form field information, and visualize form fields in documents.

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