发现我们为 database management 精心策划的 MCP 服务器集合。浏览 1319 个服务器,找到满足您需求的完美 MCP。
Provides semantic memory and persistent storage capabilities for Claude using ChromaDB and sentence transformers.
Connects AI agents to databases, providing team's proven query patterns for collaborative learning and faster development.
Enables natural language interaction with Neo4j databases and Aura accounts using the Model Context Protocol.
Connects to MongoDB databases and MongoDB Atlas clusters via the Model Context Protocol.
Provides an MCP server to interact with ClickHouse databases.
Connects Elasticsearch data to any Model Context Protocol (MCP) Client, enabling natural language interaction.
Exposes PostgreSQL databases to AI agents via the Model Context Protocol, offering rich schema discovery and query capabilities.
Exposes databases to AI agents and LLM-powered applications via MCP or OpenAPI 3.1 protocols.
Enables AI assistants to safely query any PostgreSQL database using natural language, returning structured SQL results.
Enables natural language interaction with the Neon Management API and databases through the Model Context Protocol.
Enables interaction with OpenSearch clusters using Python.
Provides a Model Context Protocol (MCP) server implementation with database capabilities powered by Chroma for LLM applications.
Enables SQL analytics capabilities for Claude by integrating MotherDuck and local DuckDB.
Connects large language models to relational databases, enabling exploration, query assistance, and data analysis.
Enables AI systems to interact with Airtable bases for reading and writing data.
Enables AI assistants to interact with multiple databases simultaneously through a unified interface.
Enables AI agents to manage and search data within Redis using natural language.
Enables enhanced MySQL operations with anomaly analysis and custom tool extension capabilities.
Empowers LLM agents with intelligent project and task management by leveraging a Neo4j graph database and the Model Context Protocol.
Enables Large Language Models (LLMs) to interact with MongoDB databases for schema inspection and operation execution.
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