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Postgres MCP Pro

by BACH-AI-Tools
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Python
Hybrid

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    Deploy Server
    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

    B3.3/5.0

    Scored across 9 tools

    Disambiguation4/5

    Most tools have distinct purposes, such as analyze_db_health for health checks and execute_sql for query execution, but analyze_query_indexes and analyze_workload_indexes could be confused as both focus on index recommendations, though their scopes differ (specific queries vs. workload analysis).

    Naming Consistency5/5

    All tool names follow a consistent snake_case pattern with clear verb_noun structures, such as analyze_db_health, execute_sql, and list_objects, making them predictable and easy to understand.

    Tool Count5/5

    With 9 tools, the set is well-scoped for a Postgres database management server, covering key areas like health analysis, query optimization, schema exploration, and SQL execution without being overwhelming.

    Completeness4/5

    The tools provide strong coverage for monitoring, analysis, and query execution in Postgres, but there are minor gaps such as missing CRUD operations for database objects (e.g., create_table or drop_schema) that agents might need to work around.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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