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A service for interpreting files and PDF documents to generate insights and summaries

  • Why this server?

    Can interpret files and PDFs through Dify workflows to generate insights and summaries.

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    license
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    Server for using Dify. It achieves the invocation of the Dify workflow by calling the tools of MCP.
    188
    Python
  • Why this server?

    Supports summarization for plain text, web pages, PDF documents, EPUB books, and HTML content, providing summaries and insights.

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    MCP Server for AI Summarization, Support for multiple content types: * Plain text * Web pages * PDF documents * EPUB books * HTML content
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    9
    9
    JavaScript
  • Why this server?

    Supports document format conversion including PDF, DOCX, Markdown and HTML allowing conversion to more easily parsed formats.

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    MCP server for seamless document format conversion using Pandoc, supporting Markdown, HTML, PDF, DOCX (.docx), csv and more.
    1
    104
    Python
    MIT License
    • Apple
  • Why this server?

    Searches and reads PDF and Word files in Box, enabling analysis of documents stored in Box.

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    The Box MCP Server facilitates searching and reading PDF and Word files in Box using Developer Token authentication.
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    2
    JavaScript
    BSD 3-Clause
  • Why this server?

    Enables LLMs to search, retrieve, and manage documents through Rememberizer's knowledge management API, allowing summarization and insight generation.

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    quality
    A Model Context Protocol server enabling LLMs to search, retrieve, and manage documents through Rememberizer's knowledge management API.
    19
    Python
    Apache 2.0
  • Why this server?

    Provides RAG capabilities for semantic document search using Qdrant, enabling users to add, search, list, and delete documentation with metadata support, thus generating insights.

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    Provides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings, allowing users to add, search, list, and delete documentation with metadata support.
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    4
    TypeScript
    Apache 2.0
  • Why this server?

    Allows for extracting pages, searching PDFs, merging PDFs, and finding related PDFs, which facilitates interpreting PDFs.

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    mcp using PyPDF2 to: • merge-pdfs • extract-pages • search-pdfs • merge-pdfs-ordered (merge in user spec. order) • find-related-pdfs (regex extracted text for related PDF files)
    5
    19
    Python
    The Unlicense
  • Why this server?

    Provides tools for reading and extracting text from PDF files, supporting both local files and URLs.

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    license
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    quality
    Provides tools for reading and extracting text from PDF files, supporting both local files and URLs.
    3
    Python
  • Why this server?

    Extracts webpage content, removes ads and non-essential elements, and transforms it into clean, LLM-optimized Markdown facilitating analysis.

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    A Python implementation of an MCP server that extracts webpage content, removes ads and non-essential elements, and transforms it into clean, LLM-optimized Markdown.
    1
    Python
    MIT License
    • Linux
    • Apple
  • Why this server?

    Enables AI to interact with markdown documentation files, providing capabilities for document management, search, and documentation health analysis.

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    license
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    quality
    A Model Context Protocol implementation that enables AI assistants to interact with markdown documentation files, providing capabilities for document management, metadata handling, search, and documentation health analysis.
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    346
    11
    TypeScript
    MIT License
    • Apple
    • Linux