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postgres-aiops

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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

    A3.6/5.0

    Scored across 35 tools

    Disambiguation4/5

    Most tools have clearly distinct resource/action targets: cancel_query vs terminate_backend, top_queries vs slow_query_rca, and the index diagnostics are separable. However, table_bloat, bloat_and_vacuum_analysis, and autovacuum_status overlap heavily around dead-tuple/vacuum diagnostics, and several index tools require careful reading to distinguish.

    Naming Consistency4/5

    All tool names consistently use snake_case, so there is no camelCase/snake_case mixing. The pattern is not uniform verb_noun: some are noun-phrase diagnostics (long_running_queries, index_bloat, table_sizes) while write tools use verbs (run_vacuum, create_index, drop_index, update_setting), making it mostly consistent with minor deviations.

    Tool Count2/5

    35 tools is far above the 3-15 well-scoped range and exceeds the 25+ 'too many' threshold. While Postgres operations is broad, many read-only diagnostic tools (table_bloat, autovacuum_status, index_bloat, etc.) could be consolidated or deferred behind a single analysis tool, so the surface feels heavy.

    Completeness4/5

    The set covers core operational read/write workflows: activity/locks/queries, index maintenance, vacuum/analyze, settings, replication/WAL, and a reversible-write/undo mechanism. Missing pieces like database/role lifecycle DDL, backup/restore, and schema introspection are notable but likely outside a focused AIOps scope, so the surface is mostly complete with minor gaps.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

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