Discover our curated collection of MCP servers for database management. Browse 2132 servers and find the perfect MCPs for your needs.
Provides AI assistants with a secure and structured way to explore and analyze ClickHouse databases.
Enables AI assistants to directly query and analyze MongoDB databases through standardized Model Context Protocol (MCP) tools and resources.
Enables Large Language Models to query local Nostr databases using the `ndb` command-line tool.
Serves search queries against a SQLite database of the Quran.
Enables LLM applications to seamlessly access and utilize Milvus vector database functionality via the Model Context Protocol.
Enables AI models to interact with MySQL databases through a standardized Model Context Protocol interface.
Provides access to a MySQL database, allowing agents to execute SQL queries.
Provides a Model Context Protocol server to access the Tsurugi database.
Accepts todo requests via FastMCP and stores them in MongoDB.
Enables LLMs to interact with YugabyteDB by listing tables, schema, row counts, and running read-only SQL queries.
Connects AI assistants to Microsoft SQL Server databases, offering 23 advanced tools for comprehensive database exploration and management.
Provides a streamable HTTP server for ZenStack applications, enabling secure, auto-generated CRUD operations with integrated authorization and authentication.
Connects Large Language Models to Kuzu databases, enabling schema inspection and query execution through the Model Context Protocol.
Enables execution of SQL queries on PostgreSQL databases via an MCP-compatible client with configurable read-only or write access.
Provides a standardized interface for SQLite database interactions, enabling schema introspection, query execution, and database modifications.
Navigates BigQuery datasets and tables, optimized for efficient LLM interaction in large projects.
Connects diverse data sources with Large Language Models using the Multi-Context Protocol, enabling intelligent querying and retrieval-augmented generation for an AI agent framework.
Simplifies common tasks in Go development through a modular utility library.
Exposes LDAP directories via the Model Context Protocol (MCP) to enable client-side directory searches and CRUD operations.
Establishes a shared, persistent memory layer for AI agents, enabling them to recall user preferences and past interactions across various platforms.
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