"Extracting Orders from PDF Files" matching MCP servers:

A PDF MCP server for extracting text, rendered pages, tables, links, annotations, outlines, metadata, and text statistics from PDF files.

Enables parsing PDF files from local paths or URLs into structured JSON or Markdown format using NetMind's AI-powered PDF extraction service.

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 deterministic, schema-driven structured data extraction from PDF documents via regex/heuristic matching, enabling repeatable, inspectable, and cost-free field extraction without LLM API calls.

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.

A Model Context Protocol server that enables the extraction of text, metadata, and embedded images from PDF files. It provides tools for searching text with context, reading specific pages, and counting total pages within a document.

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.

A server designed for processing PDF documents, enabling text extraction, table data retrieval, and metadata collection from local files. It allows users to scan directories for PDFs and read specific pages, specifically optimized for thesis literature analysis.

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

Enables natural language interaction with e-books, extracting metadata, table of contents, and chapter content from EPUB and PDF files.

Converts PDF files to text for use with MCP-compatible applications like Cursor IDE.

Reads PDF, image, or video files by sniffing format and delegating to specialized sibling MCP servers, extracting facts and metadata without LLMs.

MCP server that gives your Claude, Cline, or Cursor session the ability to extract text, tables, and metadata from any PDF URL — including scanned PDFs via OCR.

Enables AI agents to download, index, and semantically search PDF research papers using 8 MCP tools.

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

Enables agents to extract clean structured JSON tables from any PDF with per-cell citations to the source page.

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 deep structural analysis of ebooks by extracting core conflicts, insights, mental models, and actionable items from PDF, Markdown, or text files.

Enables researching YouTube channels and videos by listing uploads, reading transcripts, extracting frames, and searching, without needing a YouTube API key.

MCP server that enables searching and retrieving Czech university theses from theses.cz, including full-text search, metadata, and direct PDF downloads with optional cookie-based authentication.