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Scraping Langchain and Langgraph documentation

  • Why this server?

    Leverages the Oxylabs Web Scraper API to fetch and process web content, which can be used to scrape documentation.

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    A scraper tool that leverages the Oxylabs Web Scraper API to fetch and process web content with flexible options for parsing and rendering pages, enabling efficient content extraction from complex websites.
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    11
    Python
    MIT License
    • Apple
    • Linux
  • Why this server?

    Retrieves content from web pages and converts HTML to markdown, making it suitable for scraping online documentation.

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    This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.
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    34,289
    JavaScript
    MIT License
  • Why this server?

    Enables LLMs to fetch and process web content in multiple formats (HTML, JSON, Markdown, text) which is essential for scraping documentation.

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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?

    Provides Q&A capabilities by retrieving documents using natural language questions, making it suitable for scraping and querying documentation.

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    Enables querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.
    5
    JavaScript
    MIT License
    • Apple
  • Why this server?

    Aims to provide AI-assisted access to documentation, which aligns with the need to scrape and understand Langchain and Langgraph documentation.

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    A customized MCP server that enables integration between LLM applications and documentation sources, providing AI-assisted access to LangGraph and Model Context Protocol documentation.
    Python
    • Linux
    • Apple
  • Why this server?

    Allows web crawling and ingestion into a Graphlit project, facilitating the retrieval of relevant contents from the MCP client, useful for gathering Langchain/Langgraph documentation.

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    The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
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    1,732
    179
    TypeScript
    MIT License
    • Apple
  • Why this server?

    Provides RAG capabilities for semantic document search using Qdrant, making it suitable for indexing and searching documentation.

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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?

    A documentation server based on MCP protocol that provides document crawling, keyword searching, and document detail retrieval.

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    A documentation server based on MCP protocol designed for various development frameworks that provides multi-threaded document crawling, local document loading, keyword searching, and document detail retrieval.
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    37
    JavaScript
    MIT License
    • Apple
    • Linux
  • Why this server?

    Enables autonomous web content retrieval by fetching pages and following links, which is useful for systematically learning from online documentation.

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    Enables LLMs to autonomously retrieve and explore web content by fetching pages and recursively following links to a specified depth, particularly useful for learning about topics from documentation.
    TypeScript
    MIT License
  • Why this server?

    Enables searching and retrieving content from Confluence documentation systems, providing capabilities for both document searches and full page content retrieval.

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    An MCP server that enables searching and retrieving content from Confluence documentation systems, providing capabilities for both document searches and full page content retrieval.
    Python