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Postgres MCP Pro Plus

by cloudthinker-ai
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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 13 tools

    Disambiguation4/5

    Most tools have distinct purposes, but there is some overlap between analyze_query_indexes and analyze_workload_indexes, both focusing on index recommendations, which could cause confusion. However, their descriptions clarify that one analyzes specific queries while the other analyzes frequently executed queries, helping to differentiate them.

    Naming Consistency4/5

    The naming follows a consistent verb_noun pattern (e.g., analyze_db_health, execute_sql, list_schemas) with minor deviations like get_blocking_queries and get_database_overview using 'get' instead of 'list' or 'analyze'. Overall, the pattern is predictable and readable.

    Tool Count5/5

    With 13 tools, the count is well-scoped for a Postgres database management server, covering analysis, execution, and listing functions. Each tool appears to serve a specific purpose without feeling excessive or insufficient for the domain.

    Completeness5/5

    The tool set provides comprehensive coverage for Postgres database management, including health analysis, query optimization, schema exploration, and SQL execution. There are no obvious gaps; it supports CRUD-like operations and lifecycle management through tools like execute_sql and various analysis functions.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources