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Using large language models to analyze and guide bid document preparation

  • Why this server?

    This server supports document format conversion using Pandoc, including converting documents to formats suitable for LLM processing (e.g., Markdown, HTML, text).

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    security
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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?

    This server can search and read PDF and Word files in Box, allowing access to the content of the documents for analysis by the LLM.

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    security
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    The Box MCP Server facilitates searching and reading PDF and Word files in Box using Developer Token authentication.
    6
    2
    JavaScript
    BSD 3-Clause
  • Why this server?

    This server enables LLMs to search, retrieve, and manage documents through Rememberizer's knowledge management API, useful for accessing previously analyzed documents or storing processed information.

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    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?

    This server provides access to multiple search engines and AI tools, which could help find information needed for the bid process or for general information.

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    🔍 A Model Context Protocol (MCP) server providing unified access to multiple search engines (Tavily, Brave, Kagi), AI tools (Perplexity, FastGPT), and content processing services (Jina AI, Kagi). Combines search, AI responses, content processing, and enhancement features through a single interface.
    15
    47
    30
    TypeScript
    MIT License
    • Linux
  • Why this server?

    This server enables fetching web content in various formats, which is essential for gathering information from company websites or online resources relevant to the bid.

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    Provides functionality to fetch web content in various formats, including HTML, JSON, plain text, and Markdown.
    4
    137,083
    150
    TypeScript
  • Why this server?

    Allows the LLM to directly access and read the contents of the documents (e.g., bid documents, company profiles) from the file system, which can then be analyzed.

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    An MCP server that allows Claude AI to perform filesystem operations including reading, writing, listing, moving files, and searching directories within specified allowed paths.
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    1
    JavaScript
  • Why this server?

    This server provides capabilities to fetch web content and converting HTML to markdown, useful if company information is online.

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    security
    A
    license
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    Enables retrieval and processing of web page content for LLMs by converting HTML to markdown, with support for content truncation and pagination.
    1
    1
    Python
    MIT License
  • Why this server?

    Provides tools for reading and extracting text from PDF files, essential for processing many bid documents and company profiles.

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

    Enables retrieval of search results from multiple search engines, allowing access to a broader range of relevant information for bid preparation.

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    An MCP server that integrates with SerpApi to retrieve search results from multiple search engines including Google, Bing, Yahoo, and others, enabling fast access to both live and archived search data.
    Python
  • Why this server?

    Provides tools for working with PDF files. Can extract pages, search PDFs and more.

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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