"A tool for PostgreSQL database querying and schema inspection" matching MCP servers:

Enables AI applications to securely access and manage PostgreSQL data in Azure via MCP tools for querying, updating, and schema operations.

A Model Context Protocol (MCP) Server that allows AI models to securely interact with data hosted in Azure Database for PostgreSQL. It enables natural language querying, schema exploration, and data management through MCP clients like Claude Desktop and Visual Studio Code.

MCP server for querying and managing multiple databases (SQLite, PostgreSQL, MySQL) with read-only mode and schema inspection.

A read-only MCP server for PostgreSQL schemas and their git history, enabling AI agents to inspect schema details, migrations, ERDs, missing indexes, circular foreign keys, and churn without write access.

MCP server for multiple databases (PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis) with tools for schema inspection, querying, performance diagnostics, and safe write operations, featuring access modes, PII masking, and audit logging.

A read-only MCP server that enables AI agents to explore database schemas and execute safe queries on PostgreSQL and MySQL.

Enables AI applications to run SQL queries and retrieve results from Oracle Database.

An MCP server that provides targeted PostgreSQL schema access to AI agents, retrieving only relevant tables for a question and enforcing read-only access through multiple layers.

Schema-aware MCP server for Accurate Online, providing tools to list resources, lookup endpoint schemas, make authenticated API calls, and refresh database host resolution.

Enables SQL database interaction with true server-side result paging, runtime-managed connection profiles, and SSH-bridged access for PostgreSQL.

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.

An MCP server that provides persistent memory for database schemas by storing table structures and metadata in a local SQLite file. It enables LLMs to save, retrieve, and manage database snapshots to maintain a structured understanding of database architectures.

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.

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.

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 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 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.