"How to perform SELECT queries in PostgreSQL" matching MCP servers:

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enables Claude Desktop to connect to PostgreSQL databases, allowing users to query, explore schemas, and analyze data using plain English without writing SQL.

Enables 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.

A secure MCP server that lets AI assistants directly interact with PostgreSQL databases via tools like create_table, list_tables, and execute_sql, plus a web configurator for managing connections.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Enables natural language interaction with PostgreSQL databases through Amazon Q for querying data, listing tables, and describing schemas. It provides secure, read-only access with automatic row limits to ensure efficient database exploration.

A Python MCP server that enables schema discovery, read-only SQL queries, table previews, and index/relationship analysis on PostgreSQL databases.

Provides long-term memory for AI agents via MCP tools to store, recall, and delete memories, with per-user scoping and usage limits.

Enables secure, read-only PostgreSQL database interaction through natural language, with automatic database discovery and connection management.

Enables AI agents to interact with PostgreSQL databases over HTTP/JSON-RPC, supporting SQL queries, schema introspection, table/index analysis, EXPLAIN query planning, role and privilege inspection, and database monitoring.

A postgresql mcp that you can run your DQL SQL though it

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.

Enables AI assistants to perform read-only PostgreSQL DBA analysis and monitoring through natural language, covering performance, bloat, locks/deadlocks, autovacuum, and schema inspection across PostgreSQL 12-18 without required extensions.

Enables AI assistants to perform PostgreSQL database operations, monitoring, and management via natural language, covering performance analysis, bloat detection, lock/deadlock monitoring, autovacuum and schema inspection with read-only production-safe queries.

Enables AI assistants to perform read-only PostgreSQL DBA work across versions 12–18, including performance analysis, slow query identification, bloat detection, lock and deadlock monitoring, autovacuum and schema inspection, and replication/WAL checks via natural language. Works with regular user permissions on RDS/Aurora without requiring any extensions, while optionally leveraging pg_stat_statements and pg_stat_monitor for deeper query analytics.

Enables AI assistants to perform PostgreSQL database operations and monitoring through natural language, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum checks, and schema inspection across PostgreSQL 12–18 without extensions.

Enables AI assistants to perform read-only PostgreSQL DBA and monitoring tasks, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum and schema inspection across PostgreSQL 12–18. It supports natural-language queries against production-safe, RDS/Aurora-compatible connections, with optional query analytics via pg_stat_statements or pg_stat_monitor.

Enables AI assistants to perform PostgreSQL database operations and monitoring through natural language, including performance analysis, bloat detection, lock and connection monitoring, autovacuum intelligence, and schema/relationship discovery. Works read-only across PostgreSQL 12-18 with no extensions required, with optional pg_stat_statements and pg_stat_monitor support for advanced query analytics.

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.

Enables AI assistants to perform PostgreSQL database operations and monitoring through natural language, including performance analysis, bloat detection, lock and deadlock monitoring, autovacuum and schema inspection across PostgreSQL 12-18.