Postgres MCP Pro Plus
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- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to manage, monitor, and optimize PostgreSQL databases with over 200 specialized tools for operations, security, performance tuning, and diagnostics.32 npm12MIT
- FlicenseNot gradedqualityAmaintenanceEnables 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. Supports PostgreSQL 12-18 with read-only production-safe tools and optional extension-enhanced query analytics.-
- FlicenseNot gradedqualityAmaintenanceEnables 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.-
- FlicenseNot gradedqualityAmaintenanceEnables AI assistants to inspect and monitor PostgreSQL databases with read-only DBA tools for performance analysis, bloat detection, locks/deadlocks, autovacuum, schema discovery, replication, and maintenance recommendations.-
- AlicenseAqualityBmaintenanceEnables comprehensive PostgreSQL database monitoring, analysis, and management through natural language queries. Provides performance insights, bloat analysis, vacuum monitoring, and intelligent maintenance recommendations across PostgreSQL versions 12-17.38164MIT
- AlicenseBqualityDmaintenanceEnables comprehensive PostgreSQL database management including index tuning, query plan analysis, health monitoring, schema-aware SQL generation, and safe SQL execution with configurable access control for both development and production environments.9MIT
TDQS
Scored across 13 tools
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.
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.
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.
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.