Enables an MCP-compatible client to execute PostgreSQL queries and receive structured results.
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This project provides a Model Context Protocol (MCP) server that allows external AI models and tools to interact with a PostgreSQL database in a standardized way. By eliminating the need for custom integrations, it offers a common API for running both `SELECT` and non-`SELECT` SQL queries, returning results in structured JSON. This enables seamless use of PostgreSQL as a knowledge base or application datastore for MCP-compatible clients.
Key Features
01Features structured logging with Loguru.
02Returns query results in structured JSON format.
031 GitHub stars
04Executes direct PostgreSQL queries via MCP.
05Supports both data retrieval (SELECT) and database modifications (INSERT, UPDATE, DELETE, CREATE).
06Operates in either standard I/O (stdio) or HTTP (REST API) modes.
Use Cases
01Integrate PostgreSQL as a data source for MCP-compatible AI models.
02Allow external MCP clients to execute SQL queries on a PostgreSQL database.
03Utilize PostgreSQL as a standardized knowledge base or application datastore for MCP systems.
