PostgreSQL MCP

PostgreSQL MCP gives your AI assistant direct, read-oriented access to PostgreSQL databases. Instead of context-switching between your editor and a database client, you can ask your AI to inspect table structures, run queries, and explain execution plans — all within the same conversation where you are writing code. This tight integration between database exploration and code generation dramatically speeds up data-layer development. The server exposes a focused set of tools designed around the most common database tasks during development. You get schema introspection through `list_tables`, `list_schemas`, and `describe_table`, which let the AI understand your data model before writing any queries. The `query` tool executes SQL and returns formatted results, while `explain_query` shows the execution plan so the AI can help you optimize slow queries with concrete data rather than guesswork. Security is handled through the connection string you provide at startup. The server connects to exactly one database with whatever permissions that connection string grants. For development workflows, this typically means connecting to a local or staging database. There is no write-access restriction at the MCP level, so use a read-only database user if you want to ensure the AI cannot modify data — a best practice that takes just one SQL command to set up.