StarRocks MCP Server
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- AlicenseBqualityBmaintenanceEnables AI assistants to connect to StarRocks databases for direct SQL execution, schema exploration, and data visualization.11Apache 2.0
- FlicenseNot gradedqualityAmaintenanceIt bridges AI assistants and StarRocks databases, enabling direct SQL execution, database/schema exploration, system metric access, detailed table/database overviews, and Plotly chart generation without complex client-side setup.-
- FlicenseNot gradedqualityAmaintenanceActs as a bridge between AI assistants and StarRocks databases, enabling direct SQL execution, listing databases and tables, retrieving table schemas and system metrics, generating data overviews with sample rows, and rendering query results as Plotly charts — all without complex client-side setup.-
- FlicenseNot gradedqualityAmaintenanceActs as a bridge between AI assistants and StarRocks databases, enabling direct SQL execution, database and table exploration, schema/data overviews, and metric access without complex client-side setup. It also generates Plotly charts from query results and caches overviews in memory for faster repeated requests.-
- FlicenseNot gradedqualityAmaintenanceEnables AI assistants to query and explore StarRocks databases, inspect schemas, metrics, and sample data, and generate Plotly charts from query results without complex client-side setup.-
- FlicenseNot gradedqualityAmaintenanceEnables AI assistants to connect to StarRocks databases for direct SQL execution, schema and database exploration, system metrics access, and Plotly chart generation. It also provides cached table and database overviews.-
TDQS
Scored across 8 tools
Each tool targets a distinct function: query execution, analysis, chart generation, schema summary, etc. There is slight overlap between read_query and query_and_plotly_chart, but their outputs differ (raw data vs chart), and descriptions clarify the distinction. No major confusion.
Tool names follow no consistent pattern: some are verb_noun (e.g., read_query), some are noun_verb (e.g., db_summary), some include conjunctions (query_and_plotly_chart), and verbs vary (analyze, collect, set, write). This inconsistency may confuse an agent trying to infer tool purposes from naming.
With 8 tools, the server is well-scoped for a database MCP server covering querying, analysis, schema browsing, and charting. Each tool serves a clear purpose without being excessive or minimal.
The tool set covers core database interactions: query (read and write), analysis, schema overview, and charting. A minor gap is the absence of a tool to list all databases, but db_summary and set_session_db partially address this. Overall, the surface is reasonably complete for the stated purpose.