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⇱ Local RAG system for providing documentation to a large language model (LLM) | Glama

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Local RAG system for providing documentation to a large language model (LLM)

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  • Why this server?

    Integrates LLMs with RAG data sources using Sionic AI's Storm Platform, essential for connecting to various document repositories.

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    An open protocol server that implements Anthropic's Model Context Protocol to enable seamless integration between LLM applications and RAG data sources using Sionic AI's Storm Platform.
    Last updated
    40

  • Why this server?

    Facilitates integration of PrivateGPT, enabling chat functionalities and secure management of knowledge sources for local RAG.

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    Facilitates integration of PrivateGPT with MCP-compatible applications, enabling chat functionalities and secure management of knowledge sources and user access.
    Last updated

  • Why this server?

    Enables semantic search and RAG over Apple Notes, allowing AI assistants to reference your notes during conversations.

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    A Model Context Protocol server that enables semantic search and RAG over your Apple Notes, allowing AI assistants like Claude to search and reference your notes during conversations.
    Last updated
    211
    10
    MIT

  • Why this server?

    Provides RAG capabilities for semantic document search using Qdrant vector database and Ollama/OpenAI embeddings.

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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.
    Last updated
    10
    16

  • Why this server?

    Provides an API to query Large Language Models using context from local files, supporting various models and file types.

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    This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.
    Last updated
    1

  • Why this server?

    Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers.

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    Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.
    Last updated
    3
    1,911
    Apache 2.0

  • Why this server?

    Vectorize MCP server for advanced retrieval, Private Deep Research, Anything-to-Markdown file extraction and text chunking.

  • Why this server?

    A Python-based MCP server that crawls websites to extract and save content as markdown files, with features for mapping website structure and links.

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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.
    Last updated
    4
    MIT

  • Why this server?

    A tool for Model Context Protocol (MCP) that allows you to analyze web content and add it to your knowledge base, storing content as Markdown files for easy viewing with tools like Obsidian.

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    A tool for Model Context Protocol (MCP) that allows you to analyze web content and add it to your knowledge base, storing content as Markdown files for easy viewing with tools like Obsidian.
    Last updated
    3
    10
    MIT