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Information or Products Related to Rags

  • Why this server?

    This server is specifically designed for RAG pipelines, enabling web browsing for LLMs similar to web search in ChatGPT.

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    Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.
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    JavaScript
    Apache 2.0
    • Apple
  • Why this server?

    This server enables RAG over documents using LanceDB.

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    A Model Context Protocol (MCP) server that enables LLMs to interact directly the documents that they have on-disk through agentic RAG and hybrid search in LanceDB. Ask LLMs questions about the dataset as a whole or about specific documents.
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    TypeScript
    MIT License
    • Apple
  • Why this server?

    Enables LLMs to perform semantic search and document management using ChromaDB, supporting natural language queries with similarity metrics for retrieval augmented generation applications.

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    Enables LLMs to perform semantic search and document management using ChromaDB, supporting natural language queries with intuitive similarity metrics for retrieval augmented generation applications.
    Python
    • Apple
  • Why this server?

    This server retrieves and process documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.

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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
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    TypeScript
    MIT License
  • Why this server?

    A Model Context Protocol server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.

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    A Model Context Protocol (MCP) server that enables semantic search and retrieval of documentation using a vector database (Qdrant). This server allows you to add documentation from URLs or local files and then search through them using natural language queries.
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    JavaScript
    Apache 2.0
    • Apple
  • Why this server?

    Integrates Jina.ai's Reader API with LLMs for efficient and structured web content extraction, optimized for documentation and web content analysis.

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    Integrates Jina.ai's Reader API with LLMs for efficient and structured web content extraction, optimized for documentation and web content analysis.
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    JavaScript
    MIT License
    • Linux
  • Why this server?

    Enables efficient web search integration with Jina.ai's Search API, offering clean, LLM-optimized content retrieval with support for various content types and configurable caching.

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    Enables efficient web search integration with Jina.ai's Search API, offering clean, LLM-optimized content retrieval with support for various content types and configurable caching.
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    JavaScript
    MIT License
  • Why this server?

    A Model Context Protocol (MCP) server implementation for Axiom that enables AI agents to query your data using Axiom Processing Language (APL).

    Axiomofficial

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    A Model Context Protocol server implementation for Axiom that enables AI agents to query your data using Axiom Processing Language (APL).
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    MIT License
  • Why this server?

    The server facilitates access to Julia documentation and source code through Claude Desktop, allowing users to retrieve information on Julia packages, modules, types, functions, and methods.

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    The server facilitates access to Julia documentation and source code through Claude Desktop, allowing users to retrieve information on Julia packages, modules, types, functions, and methods.
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    2
    JavaScript
    MIT License
  • Why this server?

    Enables vector similarity search and serving of Svelte documentation via the MCP protocol, with support for local caching and multiple llms.txt documentation formats.

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    Enables vector similarity search and serving of Svelte documentation via the MCP protocol, with support for local caching and multiple llms.txt documentation formats.
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    TypeScript
    MIT License