"Information or resources related to PostgreSQL" matching MCP servers:

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

A general-purpose PostgreSQL MCP server with full read-write SQL access, atomic multi-statement transactions, and schema inspection. Works with any PostgreSQL instance — local, Supabase, AWS RDS, or self-hosted — and connects to Claude, Cursor, Windsurf, or any MCP-compatible AI client.

Full-featured MCP server that exposes 36 tools for interacting with PostgreSQL databases, covering schema introspection, query execution, data exploration, performance monitoring, security auditing, and maintenance.

A Model Context Protocol server that enables interaction with PostgreSQL databases for analyzing setups, debugging issues, managing schemas, migrating data, and monitoring performance.

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 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 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 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 inspect and monitor PostgreSQL databases with read-only DBA tools for performance analysis, bloat detection, locks/deadlocks, autovacuum, schema discovery, replication, and maintenance recommendations.

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.

Enables AI assistants to inspect and monitor PostgreSQL 12–18 databases through natural language, covering performance and slow-query analysis, table bloat detection, connection/lock and deadlock monitoring, autovacuum and VACUUM effectiveness, replication/WAL status, and schema and relationship discovery. All operations are read-only and production-safe, working with regular user permissions on RDS/Aurora, with optional pg_stat_statements and pg_stat_monitor extensions for deeper query analytics.

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

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. Supports PostgreSQL 12-18 with read-only production-safe tools and optional extension-enhanced query analytics.

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.

Enables Claude Desktop to interact with PostgreSQL databases through natural language for schema exploration, data analysis, and query execution. Users can search schemas, describe tables, and perform read or write operations without needing to write manual SQL.

Enables AI assistants to perform read-only PostgreSQL DBA operations through natural language, including performance and slow-query analysis, bloat and capacity detection, lock/deadlock and connection monitoring, autovacuum/VACUUM effectiveness checks, and schema and relationship discovery. It works across PostgreSQL 12-18 with automatic version detection and no required extensions, optionally enhancing query analytics via pg_stat_statements or pg_stat_monitor.

Enables AI assistants to perform PostgreSQL operations and monitoring through natural language, including performance analysis, bloat detection, lock/deadlock monitoring, autovacuum inspection, schema discovery, and maintenance recommendations with production-safe read-only tools across PostgreSQL 12–18.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables AI assistants to convert CSS-animated SVGs into videos (MP4/WebM/MKV/MOV) and animated images (aPNG/GIF) with frame-accurate rendering and transparency support.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables AI clients to interact with PostgreSQL databases through natural language, translating requests into structured queries and returning results via a secure self-hosted server.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.

Enables existing Express routers to be exposed as MCP tools, dispatching tool calls through the Express middleware stack in-process without a network hop.

Turns any OData V2 or V4 service, SAP Gateway included, into MCP tools that AI clients such as Claude, ChatGPT, Copilot, and Cursor can call without code by reading $metadata. It lets models discover entity sets and fields, then query services through built-in read-only tools.

Auto-generates MCP tools from your OpenAPI spec, allowing natural language interaction with any API via configurable headers and serverless deployment.