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"Connecting to a Surreal database" matching MCP servers:

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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.
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    Apache 2.0
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    askDB is an MCP server that retrieves relevant database schema (DDL) from a Pinecone index and provides it to LLMs to write SQL, without connecting to the database itself.
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    Enables LLMs to interact with Zvec vector database through tools for collection management, document operations, vector search, and AI-powered embeddings.
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    Apache 2.0
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    Provides semantic search capabilities by connecting Claude Desktop to a Cloudflare Workers backend powered by Vectorize. It enables natural language querying of knowledge bases using vector similarity and edge-based embedding generation.
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    MIT
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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.
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    Apache 2.0
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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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    MIT
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    A lightweight server implementation of the Model Context Protocol that connects Memgraph database with LLMs, allowing users to interact with graph databases through natural language.
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    An example server that enables interaction with Alibaba Cloud's Lindorm multi-model NoSQL database, allowing applications to perform vector searches, full-text searches, and SQL operations through a unified interface.
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    Apache 2.0
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    MCP server for Vectros, a typed multi-tenant record store with hybrid search and citation-grounded RAG, enabling agents to query, search, and ask questions over their own indexed data.
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    Apache 2.0
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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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    Apache 2.0
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    MCP server for Qdrant vector database with local BERT embeddings. Enables semantic search and vector storage operations through natural language.
    MIT
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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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    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.
    MIT