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An open-source vector database for similarity search and AI applications

  • Why this server?

    This server is specifically designed to create an MCP server for Qdrant, a vector search engine, which directly addresses the user's search query.

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    This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
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    448
    Python
    Apache 2.0
  • Why this server?

    This server provides a Machine Control Protocol server that enables storing and retrieving information from a Qdrant vector database, matching the user's need for interacting with Qdrant.

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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.
    • Linux
    • Apple
  • Why this server?

    Provides tools for listing and retrieving content from different knowledge bases using semantic search capabilities, which could be useful if the user wants to use Qdrant for semantic search.

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    Provides tools for listing and retrieving content from different knowledge bases using semantic search capabilities.
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    TypeScript
    The Unlicense
    • Linux
    • Apple
  • Why this server?

    A local vector database system that provides fast, efficient semantic search capabilities, which aligns with the functionality of Qdrant as a vector search engine.

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    A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.
    Python
    MIT License
  • Why this server?

    Provides semantic memory and persistent storage, leveraging ChromaDB and sentence transformers. Since Qdrant is also a vector database for semantic search, this could be an alternative the user is interested in.

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    Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.
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    167
    Python
    MIT License
    • Linux
  • Why this server?

    Provides read-only access to MySQL databases, enabling LLMs to inspect database schemas and execute read-only queries. User might be interested in this if they want to use Postgresql as metadata storage for Qdrant.

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    An enhanced Model Context Protocol server that enables LLMs to inspect database schemas with rich metadata and execute read-only SQL queries with safety checks.
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    TypeScript
    • Apple
  • Why this server?

    Offers a knowledge graph memory system with semantic search, which could be relevant for users wanting to integrate Qdrant with a knowledge graph.

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    Scalable, high-performance knowledge graph memory system with semantic search, temporal awareness, and advanced relation management.
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    TypeScript
    MIT License
  • Why this server?

    Provides vector database capabilities through Chroma, which is an alternative to Qdrant and could be useful for the user to compare options.

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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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    Python
    MIT License
    • Apple
    • Linux
  • Why this server?

    A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup. Can be used together with Qdrant.

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    A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup
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    Python
    • Apple
    • Linux
  • Why this server?

    Connects agents to Elasticsearch data using the Model Context Protocol, offering an alternative to Qdrant for indexing and searching data.

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    Connects agents to Elasticsearch data using the Model Context Protocol, allowing natural language interaction with Elasticsearch indices through MCP Clients like Claude Desktop and Cursor.
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    7
    TypeScript
    MIT License
    • Apple
    • Linux