StarRocks MCP Server

The StarRocks MCP Server acts as a seamless bridge between AI assistants and StarRocks analytical databases. It eliminates the need for developers to write custom connectors or manage complex client‑side configurations, allowing AI agents to query, explore, and visualize data directly through the MCP interface. By exposing a rich set of resources—such as for schema inspection and for internal metrics—the server gives AI assistants a first‑class view into the database structure and runtime state, empowering them to ask context‑aware questions about data distribution or performance.

Key capabilities include direct SQL execution for both read () and write (DDL/DML) operations, enabling an AI assistant to run analytics queries on demand. The server also provides database exploration tools: listing databases, tables, and retrieving detailed table schemas. For deeper insight, it offers overview endpoints (, ) that return column definitions, row counts, and sample data in a single call. These summaries are cached in memory to accelerate repeated requests, while still allowing cache bypass for fresh data.

Visualization is a standout feature: the resource executes a query and returns a Plotly chart, turning raw data into interactive graphics without leaving the MCP ecosystem. This is especially useful for AI assistants that need to present findings visually or generate dashboards on the fly.

The server integrates smoothly into existing MCP workflows. Developers can launch it via a standard MCP host, configuring connection details through environment variables or JSON command definitions. The flexible configuration supports both streamable HTTP and local development modes, making it easy to test or deploy in production. Once running, an AI assistant can simply reference the MCP server’s URL to perform any supported operation, from simple data retrieval to complex analytical visualizations.

In practice, StarRocks MCP Server is ideal for scenarios such as data‑driven chatbot analytics, automated reporting pipelines, or real‑time business intelligence where an AI assistant must interact with large analytical datasets. Its built‑in caching, direct SQL support, and chart generation give developers a powerful, low‑overhead tool to unlock the full potential of StarRocks within AI‑powered applications.