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An MCP to access OpenAI's RAG system via API

  • Why this server?

    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. It directly addresses the user's need for a RAG system.

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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 -
    5
    4
    TypeScript
    Apache 2.0
  • Why this server?

    A lightweight bridge that wraps OpenAI's built-in tools (like web search and code interpreter) as Model Context Protocol servers, enabling their use with Claude and other MCP-compatible models, if OpenAI's RAG is presented as a tool.

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    A lightweight bridge that wraps OpenAI's built-in tools (like web search and code interpreter) as Model Context Protocol servers, enabling their use with Claude and other MCP-compatible models.
    Last updated -
    8
    Python
    MIT License
    • Apple
  • Why this server?

    A bridge enabling seamless communication between Ollama's local LLM capabilities into MCP-powered applications, allowing users to manage and run AI models locally with full API coverage which allows RAG if the models support that.

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    A bridge that enables seamless integration of Ollama's local LLM capabilities into MCP-powered applications, allowing users to manage and run AI models locally with full API coverage.
    Last updated -
    10
    33
    JavaScript
    • Apple
  • Why this server?

    An open standard server implementation that enables AI Assistants to directly access APIs and services through Model Context Protocol, built using Cloudflare Workers for scalability. Could be adapted for OpenAI's API.

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    An open standard server implementation that enables AI assistants to directly access APIs and services through Model Context Protocol, built using Cloudflare Workers for scalability.
    Last updated -
    TypeScript
  • Why this server?

    A Model Context Protocol server that enables LLMs to interact with Elasticsearch clusters, allowing them to manage indices and execute search queries using natural language. Elasticsearch can be used as a datastore for RAG.

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    A Model Context Protocol server that enables LLMs to interact with Elasticsearch clusters, allowing them to manage indices and execute search queries using natural language.
    Last updated -
    1
    JavaScript
  • Why this server?

    A Model Context Protocol server that provides Claude and other LLMs with read-only access to Hugging Face Hub APIs, enabling interaction with models, datasets, spaces, papers, and collections through natural language. Useful if your RAG components are hosted on HF.

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    A Model Context Protocol server that provides Claude and other LLMs with read-only access to Hugging Face Hub APIs, enabling interaction with models, datasets, spaces, papers, and collections through natural language.
    Last updated -
    4
    Python
    MIT License
    • Apple
  • Why this server?

    A Model Context Protocol server providing unified access to multiple search engines and AI tools, combining search, AI responses, content processing, and enhancement features through a single interface. Allows searching documents in the cloud.

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    🔍 A Model Context Protocol (MCP) server providing unified access to multiple search engines (Tavily, Brave, Kagi), AI tools (Perplexity, FastGPT), and content processing services (Jina AI, Kagi). Combines search, AI responses, content processing, and enhancement features through a single interface.
    Last updated -
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    66
    40
    TypeScript
    MIT License
    • Linux
  • Why this server?

    A Model Context Protocol server providing vector database capabilities through Chroma, enabling semantic document search, metadata filtering, and document management with persistent storage, for the RAG system.

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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.
    Last updated -
    17
    Python
    MIT License
    • Apple
    • Linux