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flin-bigquery-mcp

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    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.7/5.0

    Scored across 10 tools

    Disambiguation4/5

    Tools split cleanly along metadata vs. data vs. query-execution lines, and the run_query/get_query_results pair explicitly warns against resubmission to poll, removing the classic confusion. Minor overlap remains between get_table, get_dataset and preview_table, which all read table/dataset information, though the descriptions distinguish schema metadata from bounded row previews.

    Naming Consistency4/5

    Nine of ten names follow a predictable verb_noun snake_case pattern (list_projects, get_dataset, preview_table, dry_run_query, run_query, get_query_results). health_check is the one deviation, using a noun_noun form, but it is a widely understood idiom and does not hurt readability.

    Tool Count5/5

    Ten tools is a well-scoped surface for a BigQuery server: enumeration, metadata inspection, preview, validation, execution and result polling each appear once. Nothing looks padded or redundant.

    Completeness4/5

    The core read/query lifecycle (project -> dataset -> table -> dry run -> run -> poll/paginate) is fully covered with no dead ends. Gaps are the absence of job management (cancel, list recent jobs/costs) and any write DDL/DML, which appears intentional for a read-only, cost-guarded server.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources