Skip to main content
Glama
jason-ung

starrocks-mcp

by jason-ung

Related Servers

Alternatives to starrocks-mcp

No user-submitted related servers found.

    Related Servers

    • F
      license
      Not graded
      quality
      A
      maintenance
      This MCP server bridges AI assistants with StarRocks databases, enabling direct SQL execution, schema and table exploration, system metrics access, and query-result chart visualization without complex client-side setup.
      -
    • A
      license
      A
      quality
      D
      maintenance
      A read-only MCP server for ClickHouse that enables AI agents to discover schema, sample data, and run read-only SQL queries to investigate observability data like logs, metrics, and traces.
      6
      3 npm
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      A read-only MCP server for Imply Cloud/Druid databases, enabling AI assistants to execute SQL queries, list tables, and explore dashboards and data cubes.
      12
      1
      MIT
    • A
      license
      C
      quality
      D
      maintenance
      A read-only MCP server that enables users to query Databricks SQL, browse metadata, and monitor Delta Lake tables. It also supports tracking Databricks Jobs, DLT Pipelines, and cluster metrics through natural language interfaces.
      25
      4
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      A read-only MCP server for exploratory data analysis across PostgreSQL, MySQL, and ClickHouse databases, providing safe, read-only access with comprehensive analysis capabilities.
      10
      186 PyPI
      6
      MIT

    TDQS

    A3.5/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: describe_table focuses on schema details, execute_query handles SQL execution, list_databases enumerates databases, and list_tables lists tables within a database. There is no overlap or ambiguity between these functions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (describe_table, execute_query, list_databases, list_tables) with clear, descriptive verbs and nouns. There are no deviations in naming style.

    Tool Count4/5

    With 4 tools, the count is reasonable for a database interaction server, covering core operations like listing, describing, and querying. It might be slightly thin for advanced database management, but it's well-scoped for basic functionality.

    Completeness3/5

    The tools cover essential read and query operations (list, describe, execute), but there are notable gaps for a database server, such as create/update/delete operations for databases or tables, which could limit agent workflows for full lifecycle management.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues