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⇱ A server to build a knowledge base of Node.js packages with RAG search functionality | Glama


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A server to build a knowledge base of Node.js packages with RAG search functionality

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  • Why this server?

    This server suggests the latest stable package versions when writing code, which aligns with building a knowledge base of node packages.

  • Why this server?

    This server helps in retrieving and processing documentation via vector search, a form of RAG.

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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
    Last updated
    12
    265
    MIT
  • Why this server?

    Similar to the above, this server is specific for RAG and documentation retrieval

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    Provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
    Last updated
    7
    12
    1
    MIT
  • Why this server?

    Focused on RAG with semantic vector search for documentation.

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    Enables AI assistants to enhance their responses with relevant documentation through a semantic vector search, offering tools for managing and processing documentation efficiently.
    Last updated
    12
    62
    MIT
  • Why this server?

    This option uses a vector database and allows for addition of documentation from URLs/local files for RAG.

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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.
    Last updated
    38
    135
    Apache 2.0
  • Why this server?

    Focuses on documentation retrieval and processing, and generating embeddings using ollama/OpenAI.

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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. Uses Ollama or OpenAI to generate embeddings. Docker files included
    Last updated
    23
    30
    MIT
  • Why this server?

    This is designed to fetch structured documentation for packages which is what the user is looking for

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    Facilitates LLMs to efficiently access and fetch structured documentation for packages in Go, Python, and NPM, enhancing software development with multi-language support and performance optimization.
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    141
    79
    MIT
  • Why this server?

    Facilitates agentic RAG and Hybrid search.

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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.
    Last updated
    21
    79
    MIT
  • Why this server?

    Can be used to extract context from git repositories for RAG purposes

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    Anthropic's github MCP server, but better. Support for more endpoints. Including releases and tags, pull request reviews, statuses, rate limit, gists, projects, packages, and even pull request diffs. Indented to be used with MissionSquad's MCP API for secret management (aka your access token).
    Last updated
    45
    281
    6
    MIT