Discover our curated collection of MCP servers for database management. Browse 1702servers and find the perfect MCPs for your needs.
Enables AI models to securely query relational databases like MySQL and PostgreSQL using the Model Context Protocol (MCP).
Enables querying of live Dynamics CRM data through natural language questions using LLMs like Claude Desktop.
Enables querying of live Elasticsearch data from Claude Desktop using CData JDBC Drivers through a read-only MCP interface.
Enables querying live Microsoft Dataverse data from Large Language Models using natural language via a Model Context Protocol (MCP) interface.
Connects Slack data to Claude Desktop via a read-only Model Context Protocol (MCP) Server using CData JDBC Drivers.
Exposes GitHub data to Large Language Models (LLMs) through a Model Context Protocol (MCP) interface.
Provides a unified Docker package containing 14 diverse Model Context Protocol servers for AI model integration.
Connects large language models to live Avro data sources by exposing them through a Model Context Protocol (MCP) interface.
Connects Large Language Models (LLMs) to live Oracle SCM data, enabling natural language queries without SQL.
Connects Large Language Models (LLMs) to live RSS feed data by exposing it as relational SQL models through a Model Context Protocol (MCP) interface.
Provides a comprehensive set of tools for interacting with the Treasure Data API within AI development environments.
Enables Model Context Protocol (MCP) compatible clients to interact with Cloudflare D1 databases.
Tracks, lists, and summarizes expenses efficiently using a FastMCP server.
Provides persistent key-value storage capabilities for AI agents to manage and retain information.
Simplifies PostgreSQL database management by providing global connection pooling, PgBouncer integration, and automatic password rotation for AWS RDS.
Provides secure and controlled access to SQLite databases through a standardized Model Context Protocol interface.
Simplifies PostgreSQL database interactions for large language models (LLMs) and AI agents via a secure Model Context Protocol (MCP) server, enabling efficient access to schemas, tables, and query execution.
Demonstrates Gilhari's INLINE mapping for efficient object-relational mapping, storing child JSON object attributes directly within the parent's database table to optimize one-to-one relationship queries.
Exposes USDA FoodData Central through a server interface.
Enables AI assistants to interact with PowerBI REST APIs, query data, and execute DAX queries for insights.
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