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    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.
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    Enables creative PDF generation with full design control including colors, shapes, emoji, and Unicode support. Supports everything from simple documents to artistic masterpieces using PDFKit's powerful API.
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    Enables loading, reviewing, and redacting sensitive content in PDF documents through text-based or area-based redaction methods. Supports customizable redaction appearance and saves redacted PDFs with comprehensive error handling.
    Last updated
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    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.
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    MIT
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    Enables searching and retrieving detailed information from PubMed articles using the NCBI Entrez API. Supports configurable search parameters including title/abstract filtering and keyword expansion to find relevant scientific publications.
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    Programmatic email deliverability testing for AI agents. Create inbox placement tests across Gmail, Outlook, Yahoo, Mail.ru, Yandex — get per-provider placement (Inbox/Spam/Promotions), SPF/DKIM/DMARC auth, Rspamd & SpamAssassin verdicts, DNS health (MX, PTR, DNSBL), and live SSE results.
    Last updated
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    MIT
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    Enables LLMs to read and extract content from PDF files with high-fidelity LaTeX recognition and layout awareness using a Python-based extraction engine. It includes a robust Node.js fallback and supports page range filtering for efficient processing of large documents.
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    MIT
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    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.
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    MIT
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    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.
    Last updated
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    MIT
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    Enables reading, searching, and metadata extraction from PDF files without loading the entire content into the context window. It provides efficient tools for text cleaning, page-specific extraction, and context-aware search results.
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    An MCP server for local PDF manipulation including merging, splitting, rotating, watermarking, and text extraction. It works with various MCP-compatible clients and processes PDFs entirely on-device without cloud services.
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    MIT
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    An MCP server that enables bidirectional conversion between Markdown and PDF formats, including text extraction from specific pages and metadata retrieval. It supports customizable PDF output sizes and document processing through standard MCP tools.
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