An MCP server for PostgreSQL AI-powered performance tuning with HypoPG support
Listed on its own since 2026-09-25. Until then it was part of postgresql-performance-tuner-mcp-server, where its earlier checks remain.
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# PostgreSQL Performance Tuning MCP [](https://pypi.org/project/pgtuner-mcp/) [](https://pypi.org/project/pgtuner-mcp/) [](https://www.python.org/downloads/) [](https://pypi.org/project/pgtuner-mcp/) [](https://hub.docker.com/r/dog830228/pgtuner_mcp) <a href="https://glama.ai/mcp/servers/@isdaniel/pgtuner-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@isdaniel/pgtuner-mcp/badge" /> </a> A Model Context Protocol (MCP) server that provides AI-powered PostgreSQL performance tuning capabilities. This server helps identify slow queries, recommend optimal indexes, analyze execution plans, and leverage HypoPG for hypothetical index testing. ## Features ### Query Analysis - Retrieve slow queries from `pg_stat_statements` with detailed statistics - Analyze query execution plans with `EXPLAIN` and `EXPLAIN ANALYZE` - Identify performance bottlenecks with automated plan analysis - Monitor active queries and detect long-running transactions ### Index Tuning - AI-powered index recommendations based on query workload analysis - Hypothetical index testing with **HypoPG** extension (no disk usage) - Find unused and duplicate indexes for cleanup - Estimate index sizes before creation - Test query plans with proposed indexes before implementing ### Database Health - Comprehensive health scoring with multiple checks - Connection utilization monitoring - Cache hit ratio analysis (buffer and index) - Lock contention detection - Vacuum health and transaction ID wraparound monitoring - Replication lag monitoring - Background writer and checkpoint analysis ### Vacuum Monitoring - Track long-running VACUUM and VACUUM FULL operation…
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