Amazon RDS for SQL Server uses GateRook’s SQL Server connector. With SQL authentication. For full verification, paste the Amazon RDS CA bundle.
The screenshots show GateRook 2.0.0: the Amazon RDS for SQL Server 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 RDS for SQL Server, choose its card and select Continue to configure.
Copy the RDS for SQL Server endpoint and SQL listener port. Your computer must be permitted by the instance’s network and security-group configuration.
Prepare a SQL Server login and password with access to the intended database. This connection does not use Windows or Microsoft Entra authentication.
Enter a Name, for example aws-rds-sql-server-demo. Your AI app uses this name to choose the connection.
Choose Amazon RDS for SQL Server. Enter a Name, endpoint Host, Port, User and Password.
Keep SSL mode at verify-full and paste the applicable Amazon RDS CA bundle into CA certificate (PEM).
Select Load databases, choose the intended databases and check Default schema for the database user. Use Schema allowlist for a narrower scope.
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 TLS failures, check the RDS endpoint hostname and current CA bundle. For access failures after login, check the login’s mapping and permissions in each selected database.
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 RDS for SQL Server on the endpoint and passing its connection test, ask your AI app to use aws-rds-sql-server-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 the tables on my RDS for SQL Server connection.”
- “Describe the selected RDS SQL Server table and its keys.”
- “Show ten recent records from the selected SQL Server table.”
| Tool | What it does | Starts as |
|---|---|---|
sql_list_schemas | List schemas, tables and views in the selected SQL Server database, within the connection and policy restrictions. | Read only |
sql_describe_table | Describe a SQL Server table’s columns, types, keys and indexes where available. | Read only |
sql_query | Run one validated SELECT using supported built-in T-SQL functions, then roll back the transaction. The login’s database permissions and the configured output limits still apply. | Read only |
sql_execute | Run one supported data or schema change 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.