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"Queries for MySQL Database" matching MCP servers:

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    Connects AI clients to MindsDB via the MySQL protocol to execute SQL queries, manage databases, and perform semantic searches within knowledge bases. It enables automated workflows through job scheduling and provides seamless integration with external data sources.
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    11
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    Enables AI agents to interact with an embedded graph database (GrafeoDB) via the Model Context Protocol, providing tools for graph CRUD, GQL queries, full-text and vector search, and graph algorithms.
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    23
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    Apache 2.0
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    An MCP server that enables LLMs to perform semantic and fulltext searches within Neo4j while executing complex, search-augmented Cypher queries for GraphRAG applications. It provides tools for database schema discovery and supports multi-provider embeddings to facilitate advanced graph traversals.
    Last updated
    5
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    MIT
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    Integrates Redshift database query capabilities with vector-based knowledgebase tools for semantic search and RAG applications. It enables users to execute SQL queries, explore database schemas, and perform hybrid semantic searches on markdown files stored in S3.
    Last updated
    7
    MIT
  • A
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    Model Context Protocol server for RosalindDB, enabling AI clients to create datasets, ingest vectors, run similarity queries, and check usage on a cost-optimized vector search database.
    Last updated
    11
    14
    Apache 2.0
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    A server that provides access to Baidu Cloud Vector Database functionality through the Model Context Protocol, enabling LLM applications to perform vector searches and database operations via natural language.
    Last updated
    14
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    Apache 2.0
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    A production-grade Model Context Protocol server for PostgreSQL. Lets AI agents safely inspect, query, operate, and tune a Postgres database — over 100 tools spanning catalog introspection, query intelligence, natural-language SQL, structural diffs, hybrid search, graph queries, data movement, live ops, and more.
    Last updated
    100
    8
    MIT
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    Enables interaction with KDB.AI through natural language for vector database operations, similarity searches, hybrid search, and advanced data analysis.
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    1
    Apache 2.0
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    Provides intelligent, persistent memory for AI assistants with semantic search, natural language queries, and OAuth-based team collaboration, enabling context-aware conversations across multiple clients.
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    2
    Apache 2.0
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    Enables interaction with DataStax Astra DB through the Model Context Protocol. Provides database connectivity and operations for Astra DB instances via secure token-based authentication.
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    1
    MIT
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    Enables AI assistants to interact with MariaDB databases through standard SQL operations and advanced vector/embedding-based search. Supports database management, schema inspection, and semantic document storage and retrieval with multiple embedding providers.
    Last updated
    MIT
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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