Postgres
Enables an MCP-compatible client to execute PostgreSQL queries and receive structured results.
About
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
- Features structured logging with Loguru.
- Returns query results in structured JSON format.
- 1 GitHub stars
- Executes direct PostgreSQL queries via MCP.
- Supports both data retrieval (SELECT) and database modifications (INSERT, UPDATE, DELETE, CREATE).
- Operates in either standard I/O (stdio) or HTTP (REST API) modes.
Use Cases
- Integrate PostgreSQL as a data source for MCP-compatible AI models.
- Allow external MCP clients to execute SQL queries on a PostgreSQL database.
- Utilize PostgreSQL as a standardized knowledge base or application datastore for MCP systems.