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MCP PostgreSQL Operations

MCP PostgreSQL Operations

by call518
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Python
Hybrid

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    • MCP-PostgreSQL-Ops

      IsabelaRiccardi
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables natural-language monitoring and administration of PostgreSQL databases, covering performance analysis, bloat detection, lock and deadlock monitoring, autovacuum intelligence, and schema inspection. It works with PostgreSQL 12-18 and can run without extensions, with optional extensions for advanced query analytics.
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    • MCP-PostgreSQL-Ops

      henrielliott86
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI assistants to monitor and operate PostgreSQL databases through natural language queries, covering performance analysis, bloat detection, lock/deadlock monitoring, autovacuum and schema inspection, and maintenance recommendations with read-only, extension-optional workflows across PostgreSQL 12–18.
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    • MCP-PostgreSQL-Ops

      Ngoc7541
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI assistants to perform PostgreSQL database operations, monitoring, and management through natural language, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum and schema inspection, and maintenance recommendations across PostgreSQL 12-18.
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    • MCP-PostgreSQL-Ops

      tmitsotakis66
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI assistants to inspect and monitor PostgreSQL databases using natural language, covering performance analysis, bloat detection, lock/deadlock monitoring, autovacuum, schema inspection, and maintenance recommendations across PostgreSQL 12–18 without requiring extensions.
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    • MCP-PostgreSQL-Ops

      miyeonc749
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI assistants to monitor and administer PostgreSQL 12-18 through natural language, covering performance and slow-query analysis, table bloat detection, lock and connection monitoring, replication and WAL status, and VACUUM/autovacuum and schema inspection. It works read-only out of the box with automatic version detection and optional extension-enhanced query analytics.
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    • MCP-PostgreSQL-Ops

      diegororato5559
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI assistants to monitor and administer PostgreSQL 12-18 databases through natural language, covering performance and slow-query analysis, table bloat detection, connection and lock monitoring, autovacuum and maintenance recommendations, and schema discovery. All operations are read-only and work with regular user permissions, requiring no extensions unless optional query-analytics features are desired.
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    TDQS

    A3.5/5.0

    Scored across 38 tools

    Disambiguation4/5

    Most tools are cleanly scoped by object+scope (table vs index vs database vs per-backend I/O; table vs database bloat), and the detailed required/prohibited use cases help agents choose correctly. However, the five vacuum tools (get_vacuum_analyze_stats, get_vacuum_effectiveness_analysis, get_autovacuum_status, get_autovacuum_activity, get_running_vacuum_operations) overlap enough that misselection is likely for 'vacuum status'-style requests.

    Naming Consistency4/5

    Nearly all 37 monitoring tools follow a consistent get_<noun>_<qualifier> snake_case pattern that is easy to predict. The lone outlier get_prompt_template breaks both the prefix and the domain convention, and a few names are verbose but still readable.

    Tool Count2/5

    At 38 tools the surface is well beyond a comfortable range for a monitoring server and includes a crowded maintenance cluster that could be consolidated into a single parameterized tool. Several version-specific tools (async I/O, per-backend I/O, wait events, WAL summarizer) further inflate the count for narrow PG 17/18 use cases.

    Completeness4/5

    For a read-only monitoring server the coverage is strong: schema objects, tables, indexes, functions, bloat, vacuum/autovacuum, I/O, WAL, replication, locks, connections, users, and configuration are all reachable. Minor gaps remain, such as no index listing tool and no ability to inspect a query plan or run/diagnose an actual query, and get_prompt_template is unrelated dead weight.

    Maintenance

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