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StarRocks MCP Server

StarRocks MCP Server

Official
by StarRocks

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    • F
      license
      Not graded
      quality
      A
      maintenance
      It 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.
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    • F
      license
      Not graded
      quality
      A
      maintenance
      Acts 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.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Acts 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.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables 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.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables 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

    A3.6/5.0

    Scored across 8 tools

    Disambiguation4/5

    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.

    Naming Consistency2/5

    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.

    Tool Count5/5

    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.

    Completeness4/5

    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.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data