Go MCP Postgres

Overview

The Go MCP Postgres server is a lightweight, zero‑dependency implementation of the Model Context Protocol (MCP) that bridges AI assistants—such as Claude or other LLMs—to a PostgreSQL database. By exposing a set of CRUD and schema‑inspection tools, it allows conversational agents to query, modify, and introspect a Postgres instance without any intermediate language runtime or complex orchestration. This eliminates the need for Node.js, Python, or other scripting layers that are typically required to expose database functionality through an MCP interface.

Developers can start the server with a single binary and a connection string, then integrate it into their MCP configuration. The server automatically registers a collection of tools: listing databases and tables, creating or altering tables, describing table schemas, and executing read‑only or write queries. An optional read‑only mode further safeguards against accidental data modification by restricting the available tools to those that only retrieve information. This feature is particularly valuable in production or shared environments where the AI should never perform destructive operations.

A standout capability of this server is its built‑in EXPLAIN check. By default, every write query is prefixed with an statement that verifies the generated execution plan against expected patterns. This proactive safety net helps catch inefficient or potentially harmful queries before they hit the database, giving developers confidence that the LLM’s output is both correct and performant. The check can be toggled off with a flag if the user prefers to bypass this step.

The server’s multilingual support is another key advantage. Tool descriptions are automatically localized based on a language flag, making it easy to deploy in bilingual or international teams. Adding new languages is straightforward—just drop a locale file into the directory, and the MCP will surface the translated tool metadata.

In practice, this MCP server is ideal for data‑driven applications where an LLM needs to interact with real tables. Use cases include automated reporting, data exploration chatbots, or dynamic dashboards that let users ask natural‑language questions and receive up‑to‑date answers directly from the database. By encapsulating PostgreSQL access behind a simple, protocol‑compliant interface, Go MCP Postgres empowers developers to build sophisticated AI workflows without the overhead of managing database drivers or server code.