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⇱ Qdrant vector database and search engine | Glama

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Qdrant vector database and search engine

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  • Why this server?

    This server is an excellent fit as it explicitly mentions enabling 'semantic search across multiple Qdrant vector database collections' for document retrieval.

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    Enables semantic search across multiple Qdrant vector database collections, supporting multi-query capability and providing semantically relevant document retrieval with configurable result counts.
    Last updated
    46
    MIT

  • Why this server?

    This server is a perfect match as its description directly states it is an 'MCP server for Qdrant, a vector search engine'.

  • Why this server?

    This server is highly relevant because it facilitates 'knowledge graph representation with semantic search using Qdrant' and mentions 'Qdrant persistence'.

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    Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.
    Last updated
    9
    24
    MIT

  • Why this server?

    This server is a direct match, providing 'semantic memory capabilities using Qdrant vector database' for storage and retrieval.

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    Provides semantic memory capabilities using Qdrant vector database with configurable embedding providers, allowing storage and retrieval of information using vector similarity.
    Last updated
    2
    Apache 2.0

  • Why this server?

    This server is a strong match as it explicitly mentions combining 'Neo4j graph database and Qdrant vector database for powerful semantic and graph-based document retrieval'.

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    Enables querying a hybrid system that combines Neo4j graph database and Qdrant vector database for powerful semantic and graph-based document retrieval through the Model Context Protocol.
    Last updated
    62
    MIT

  • Why this server?

    This server is a good fit as it includes 'Qdrant' within its ecosystem for enhanced memory, data analytics, and infrastructure domains.

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    A production-ready MCP server ecosystem providing Claude AI with 150+ specialized tools across enhanced memory, data analytics, security, design, and infrastructure domains with PostgreSQL, Redis, Qdrant, and Docker orchestration.
    Last updated

  • Why this server?

    This server is a direct match, enabling 'semantic code search across codebases using Qdrant vector database and OpenAI embeddings'.

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    Enables semantic code search across codebases using Qdrant vector database and OpenAI embeddings, allowing users to find code by meaning rather than just keywords through natural language queries.
    Last updated
    2
    MIT

  • Why this server?

    This server is a direct match as its description states it 'enables storing and retrieving information from a Qdrant vector database with semantic search capabilities'.

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    A Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.
    Last updated
    Apache 2.0

  • Why this server?

    This server is relevant as it 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