"Extracting Orders from PDF Files" matching MCP servers:

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

Enables AI agents to extract PDF text, search with PDF++ citations, access vault files, manage tags, and run Dataview queries in Obsidian via MCP.

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.

MCP server for full-text search across PDF document collections with offline indexing, ranked results, snippets, and page rendering.

Enables a persistent local library for mathematical PDFs with cached LaTeX extraction, full-text search in English and Greek, and page/image retrieval over MCP.

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.

An MCP (Model Context Protocol) server that provides structured access to ISO 32000 (PDF) specification documents. Enables LLMs to navigate, search, and analyze PDF specifications through well-defined tools.

Enables searching Telegram messages and chats, retrieving recent messages, and extracting text from attached documents (PDF, TXT, MD, CSV) using your personal Telegram account.

Search your own files from Claude & any MCP client: PDF, Office and more. Exact full-text search with page numbers, 100% local. Needs the RootMind app.

Enables AI agents to efficiently process large local and online PDFs through selective extraction of text, images, and metadata. It provides tools for content search and document outline navigation to optimize context window usage.

Enables RAG over messy PDFs — extract, chunk, embed, and search scanned, multi-column, and table-heavy documents.

Exposes semantic search over a folder of indexed PDF guides as a tool that Claude Code or any MCP client can call. Returns the closest matching passages with relevance scores, source file and page citations, so the client can answer questions about the guides while knowing when nothing relevant was found.

A local RAG MCP server for PDF development experience, enabling document ingestion, semantic search, and Q\&A with source citations using TF-IDF and cosine similarity.

Enables assistants to search a Zotero library, retrieve metadata and PDF text, and view PDF pages as rendered images so figures and layouts are visible.

An MCP server providing comprehensive PDF processing capabilities with 18 tools for text extraction, OCR, image conversion, metadata management, and optimization.

A Model Context Protocol server that enables AI assistants to read PDF files, extract text, retrieve metadata, read specific pages, and search within PDFs.

Enables AI assistants to perform institutional research and due diligence by retrieving, extracting, validating, and citing data from public sources, then generating reports in markdown, HTML, or PDF.

Enables fetching and extracting text from URLs, searching the web via DuckDuckGo and Yandex, and retrieving page links through MCP tools.

Enables listing, reading, and searching local files and directories through MCP tools.

Enables extraction of content from various web sources including webpages, YouTube transcripts, tweet threads, PDF files, and public Google Docs. It provides specialized tools to convert internet resources into markdown or text for model consumption.

Enables searching and retrieving files from SharePoint and OneDrive within Microsoft 365, with local caching for efficiency.

Enables searching, retrieving, and parsing academic papers from arXiv, including keyword search, PDF downloads, content extraction from HTML/PDF formats, and accessing the latest AI research papers.

MCP bridge for PDF Content Search — full-text PDF search with Apple Vision OCR across thousands of documents in under a second from Claude, Cursor, or any MCP client. Advanced filters (date, category, sender, amount), wildcards, boolean operators. Bridge open-source (MIT), PDF Content Search app is commercial with free iOS+Android companion scanner apps.

Enables searching and retrieving academic papers from arXiv by various criteria including title, author, and category, with support for extracting full text content from PDFs.

Enables searching, extracting, and analyzing over 2.4 million arXiv papers, with PDF extraction via GROBID and citation network building through Semantic Scholar integration.

Provides web connectivity tools for searching the web via DuckDuckGo or SerpAPI, fetching URL content, and extracting readable text from web pages.

A Model Context Protocol (MCP) server that provides powerful RAG (Retrieval-Augmented Generation) capabilities for PDF documents. This server uses ChromaDB for vector storage, sentence-transformers for embeddings, and semantic chunking for intelligent text segmentation.

Builds searchable SQLite databases from PDFs, preserving inline image locations for AI agents to discover and caption visual content. Supports full-text search over text, image placeholders, and saved captions.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

Search job vacancies and freelance orders from freelance boards, RSS and Telegram, and retrieve market analytics via OpenRadar.