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Retrieving Markdown Files from a Database

  • Why this server?

    This server crawls websites to extract content and save it as markdown files, which is relevant for retrieving markdown from a database.

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    A Python-based MCP server that crawls websites to extract and save content as markdown files, with features for mapping website structure and links.
    1
    Python
    MIT License
  • Why this server?

    This server provides tools for extracting text from PDF files, and while it doesn't directly retrieve from a database, it helps prepare content for storage or analysis, which could involve markdown conversion.

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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?

    This server fetches web content in multiple formats (HTML, JSON, Markdown, text) with automatic format detection, which is useful for obtaining markdown files from web sources to be stored in a database.

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    A Model Context Protocol server that enables LLMs to fetch and process web content in multiple formats (HTML, JSON, Markdown, text) with automatic format detection.
    TypeScript
    • Apple
  • Why this server?

    This server helps retrieve and process content from web pages, converting HTML to markdown, useful for database storage.

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    This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.
    1
    37,968
    JavaScript
    MIT License
  • Why this server?

    This server converts Markdown to styled PDFs, which while not directly retrieving markdown, could be part of a pipeline where markdown is created and then stored.

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    Converts Markdown to styled PDFs using VS Code's markdown styling and Python's ReportLab, providing a simple note storage system with custom URI scheme.
    6
    Python
    • Apple
  • Why this server?

    An MCP server that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context (which may be stored as markdown).

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    An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context
    7
    62
    81
    TypeScript
    MIT License
  • Why this server?

    This server enables integration with Google Drive for listing, reading, and searching over files, supporting various file types with automatic export for Google Workspace files. While not directly retrieving markdown, it can access markdown files stored in Google Drive.

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    Enables integration with Google Drive for listing, reading, and searching over files, supporting various file types with automatic export for Google Workspace files.
    1,327
    9
    JavaScript
    MIT License
  • Why this server?

    This server enables LLMs to search, retrieve, and manage documents through Rememberizer's knowledge management API. This could include Markdown files stored in the system.

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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?

    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. Documentation could be in markdown.

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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.
    5
    4
    TypeScript
    Apache 2.0
  • Why this server?

    A server that allows fetching web page content using Playwright headless browser with AI-powered capabilities for efficient information extraction. Can be used to fetch the content and save as markdown.

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    security
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    A server that allows fetching web page content using Playwright headless browser with AI-powered capabilities for efficient information extraction.
    2
    926
    2
    TypeScript
    MIT License