Amazon Aurora and RDS for PostgreSQL uses GateRook’s PostgreSQL connector. With a database user and password. For full verification, paste the Amazon RDS CA bundle.
The screenshots show GateRook 2.0.0: the Amazon Aurora and RDS for PostgreSQL form, the endpoint selector, and this connector’s actual tool preview. The form and preview have not been saved. Select a screenshot to open it at full size.
1. Create a connection and enter the settings
In GateRook, open Connections, select Add connection, search for Amazon Aurora and RDS for PostgreSQL, choose its card and select Continue to configure.
Copy the PostgreSQL endpoint and port from the RDS or Aurora console. Your computer needs a route to the instance or cluster and permission through its security group.
Use a dedicated database user with access to the tables you want the AI to read. Enter its password in GateRook; do not paste it into an AI chat.
Enter a Name, for example aws-rds-postgresql-demo. Your AI app uses this name to choose the connection.
Choose Amazon Aurora and RDS for PostgreSQL. Enter a Name, the endpoint DNS name in Host, its Port, and the database User and Password.
Set SSL mode to verify-full and paste the applicable Amazon RDS CA bundle into CA certificate (PEM). Keep the endpoint hostname so certificate verification can match it.
Select Load databases, then choose only the databases this connection should expose. If loading fails because the account cannot connect to postgres, set Discovery database to a database it can access and try again.
Choose Development, Staging or Production to match the service. Review the connector’s limit and access settings before continuing.
2. Test the connection and add it to an endpoint
Select Continue to test. GateRook checks the settings from your computer. Review the result and resolve any connection, certificate or permission error before continuing.
For a timeout, check VPN or private-network reachability and the database security group. For a certificate error, check the RDS CA bundle rather than disabling verification.
After the test passes, select Continue to add to an endpoint. Choose the endpoint your AI app uses, review its tool modes, then select Save connection. GateRook offers default as the starter endpoint.
3. Use the connection from your AI IDE
After saving Amazon Aurora and RDS for PostgreSQL on the endpoint and passing its connection test, ask your AI app to use aws-rds-postgresql-demo, or the name you chose. If its tools are missing, confirm the endpoint assignment and refresh the MCP connection or start a new chat.
The preview below shows this connector’s default tools before saving. The table explains what each tool can do; connection settings, credentials and endpoint policies can restrict access further.
Start with a small read request. Replace example resource names with existing resources your connection may access. Open Activity after the call to inspect its connection, tool, arguments, policy decision and result metadata.
Ask your AI, for example
- “List tables on my RDS PostgreSQL connection.”
- “Describe the keys and indexes of the Aurora PostgreSQL table I select.”
- “Count orders by status in the selected PostgreSQL database.”
| Tool | What it does | Starts as |
|---|---|---|
sql_list_schemas | List schemas, tables and views in the selected PostgreSQL database, within the connection and policy restrictions. | Read only |
sql_describe_table | Describe a table’s columns, types, keys and indexes where available. | Read only |
sql_query | Run one validated PostgreSQL read statement in a read-only transaction, then roll it back. Function allowlists, database permissions and output limits apply. | Read only |
sql_execute | Run supported data or schema changes with Approval by default. Database permissions and the environment policy determine which changes are allowed. | Approval |
You can change each tool’s mode on the endpoint. Every call your AI makes appears in Activity.