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Information or resources related to 'rag'

  • Why this server?

    Mentions RAGFlow explicitly, suggesting it's designed for retrieval-augmented generation workflows.

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    A simple temporary MCP server for RAGFlow that bridges the gap until an official version is released.
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    1
    Python
    Apache 2.0
    • Linux
    • Apple
  • Why this server?

    Includes 'Private Deep Research' and 'text chunking', aligning with RAG principles.

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    Vectorize MCP server for advanced retrieval, Private Deep Research, Anything-to-Markdown file extraction and text chunking.
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    17
    JavaScript
    MIT License
    • Apple
    • Linux
  • Why this server?

    Connects to the Storm Platform for RAG data sources.

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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.
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    27
    Python
    • Apple
  • Why this server?

    Mentions vector database capabilities, essential for RAG.

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    A Model Context Protocol server providing vector database capabilities through Chroma, enabling semantic document search, metadata filtering, and document management with persistent storage.
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    17
    Python
    MIT License
    • Apple
    • Linux
  • Why this server?

    Explicitly described as a platform for Retrieval-Augmented Generation (RAG).

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    An open-source platform for Retrieval-Augmented Generation (RAG). Upload documents and query them ⚡
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    169
    JavaScript
    MIT License
  • Why this server?

    Uses the React Agent pattern, which is a technique to provide more structured responses, and as a result, a higher retrieval when performing RAG.

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    A simple MCP server that enables meeting room booking through an AI assistant, supporting room availability checks and booking operations with React Agent pattern for tool calling.
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    Python
  • Why this server?

    Provides access to recipe data and meal planning. Those task can be improved by using retrieval augmented generation.

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    An MCP server that transforms AI assistants into personal chefs by providing recipe recommendations and meal planning features based on the HowToCook repository.
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    229
    TypeScript
  • Why this server?

    Focuses on memory storage and retrieval, key components of RAG systems.

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    An MCP server implementation that helps Claude remember and learn from programming errors by storing, retrieving, and finding similar errors with full context.
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    2
    Python
    MIT License
    • Apple
  • Why this server?

    Provides access to documentation, beneficial when creating RAG systems that need to know about coding documentation.

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    A simple Model Context Protocol server that enables searching and retrieving relevant documentation snippets from Langchain, Llama Index, and OpenAI official documentation.
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    Python
    • Apple
    • Linux
  • Why this server?

    A bridge that connects AI assistants and search services enabling search functionality. RAG systems benefit when using a search service.

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    A bridge between AI assistants and search services that implements A2A protocol and Model Context Protocol, enabling search functionality for web, videos, maps, flights, and hotels.
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    3
    Python
    MIT License
    • Apple