Postgres MCP Pro is an open-source Model Context Protocol (MCP) server designed to enhance the entire PostgreSQL lifecycle, from development and testing to production tuning and maintenance. It provides deep database health analysis, intelligent index tuning, query plan optimization, schema-aware SQL generation, and safe SQL execution with robust access controls. The solution supports both standard input/output and server-sent events transports, enabling integration with AI agents for automated or context-aware database operations.

• ⭐ 1,487
• MCP
• crystaldba/postgres-mcp

Implements a Model Context Protocol (MCP) server enabling robust integration with Elasticsearch and OpenSearch clusters. Offers a standardized set of tools for managing indices, documents, clusters, data streams, and aliases, along with configurable authentication and operation restrictions. Supports secure access and flexible configuration via environment variables, ensuring safe and customizable operations for various deployment scenarios.

• ⭐ 223
• MCP
• cr7258/elasticsearch-mcp-server

Couchbase MCP Server provides an MCP-compliant server for connecting Large Language Models to Couchbase clusters. It supports various database operations such as bucket and collection listing, document retrieval, upsert, and deletion, as well as running SQL++ queries and retrieving index information. Designed for easy integration with MCP clients like Claude Desktop, it includes features for secure authentication and query mode configuration. The server can be deployed using a prebuilt PyPI package or directly from source.

• ⭐ 24
• MCP
• Couchbase-Ecosystem/mcp-server-couchbase

mcp-confluent is a Model Context Protocol (MCP) server implementation designed to enable natural language interaction with Confluent Cloud REST APIs. It integrates with AI tools such as Claude Desktop and Goose CLI, allowing users to manage Kafka topics, connectors, and Flink SQL statements conversationally. The project offers flexible configuration, CLI usage, and supports various transports for secure and customizable operations.

• ⭐ 115
• MCP
• confluentinc/mcp-confluent

ClickHouse MCP Server provides an MCP-compliant interface for executing SQL queries, listing databases, and managing tables on ClickHouse clusters. It supports both direct ClickHouse connections and embedded chDB engines, offering pagination, filtering, and detailed metadata in responses. Integrated health checks and flexible configuration options make it suitable for a variety of deployment scenarios.

• ⭐ 592
• MCP
• ClickHouse/mcp-clickhouse

Chroma MCP Server implements the Model Context Protocol to allow seamless integration between LLM applications and external data using the Chroma embedding database. It enables AI models to create, manage, and query collections with advanced vector search, full text search, and metadata filtering. The server supports both ephemeral and persistent client types, along with integration for HTTP and cloud-based Chroma instances. Multiple embedding functions, collection management tools, and rich document operations are available for extensible LLM workflows.

• ⭐ 418
• MCP
• chroma-core/chroma-mcp

dicom-mcp enables AI assistants and tools to query, read, and transfer data on DICOM servers, such as PACS and VNA systems. It integrates with MCP-compatible clients, offering tooling for searching patient records, retrieving medical reports, and sending image data to analysis endpoints. Configurable via YAML, it streamlines operations on DICOM databases for research and development in medical imaging. It is explicitly designed for interoperability with LLM-based AI workflows.

• ⭐ 74
• MCP
• ChristianHinge/dicom-mcp

CentralMind Gateway automatically generates secure, LLM-optimized APIs for structured databases and exposes them via REST, OpenAPI 3.1, or the Model Context Protocol (MCP), including Server-Sent Events (SSE) for AI agents. It integrates privacy protection, auditing, and authentication mechanisms to enable seamless and compliant data access for AI-powered applications. The tool supports multiple database backends and is optimized for AI workloads, providing enhanced metadata for improved context understanding.

• ⭐ 500
• MCP
• centralmind/gateway

Wren Engine is a semantic engine designed for Model Context Protocol (MCP) clients and AI agents. It enables precise access to enterprise data by providing semantic understanding, trusted aggregations, and business term clarity across numerous data sources. With a focus on accurate context, calculation, and governance, it equips AI systems to interact safely and meaningfully with complex enterprise data. As part of the MCP ecosystem, it connects LLMs with databases and enterprise tools through standardized protocols.

• ⭐ 496
• MCP
• Canner/wren-engine

mcp-server-tidb provides an implementation of the Model Context Protocol (MCP) for TiDB, enabling integration with serverless TiDB databases. It supports configuration through environment variables or .env files and connects with applications such as Claude Desktop via standardized configuration. The server facilitates managing context between conversational AI models and a TiDB backend in a consistent and standardized way.

• ⭐ 22
• MCP
• c4pt0r/mcp-server-tidb

MCP Server for MySQL - Claude Code Edition provides an implementation of the Model Context Protocol for secure, context-driven access to MySQL databases. It enables AI tools, such as Claude Code, to access and manipulate database schemas and data through SSH tunnels, supporting multi-project setups and automated management. The server offers advanced configuration options and permission controls for safe interaction with remote databases.

• ⭐ 902
• MCP
• benborla/mcp-server-mysql

CockroachDB MCP Server enables natural language interactions with CockroachDB, integrating with Model Context Protocol (MCP) clients. It supports comprehensive database management, cluster monitoring, and SQL operations through standardized tools. Designed for LLMs and agentic applications, it facilitates seamless AI-driven workflows to query, manipulate, and monitor CockroachDB databases. The system emphasizes performance, scalability, and easy integration with popular LLM tools.

• ⭐ 6
• MCP
• amineelkouhen/mcp-cockroachdb

Alibaba Cloud Tablestore MCP Servers provides multiple implementations (Java and Python) of MCP (Model Context Protocol) server-side components. It includes sample projects and a production-ready RAG-based knowledge Q&A system, enabling management of context and knowledge for AI applications on Tablestore. The libraries showcase standardized approaches for integrating Tablestore with modern AI use cases requiring context handling.

• ⭐ 148
• MCP
• aliyun/alibabacloud-tablestore-mcp-server

Query MCP server provides an open-source implementation of the Model Context Protocol (MCP) for Supabase, enabling secure execution of SQL, schema management, and project administration directly from compatible IDEs. It offers robust safety measures, runtime SQL validation, and transaction handling, supporting collaboration across MCP clients. The server empowers developers to manage Supabase projects, users, and schema while ensuring built-in safety controls.

• ⭐ 811
• MCP
• alexander-zuev/supabase-mcp-server

Aiven MCP Server implements the Model Context Protocol (MCP) to provide secure access to Aiven's PostgreSQL, Kafka, ClickHouse, Valkey, and OpenSearch services. It enables Large Language Models (LLMs) to seamlessly integrate and interact with these cloud data platforms, supporting full stack solution development. The server offers streamlined tools for project and service management via standardized APIs and supports integration with platforms like Claude Desktop and Cursor. Environment variable configuration and explicit permission controls are used to ensure secure and flexible operations.

• ⭐ 11
• MCP
• Aiven-Open/mcp-aiven