Azure SQL Database uses GateRook’s SQL Server connector. With SQL authentication over verified TLS; Microsoft Entra sign-in is not supported.
The screenshots show GateRook 2.0.0: the Azure SQL Database 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 Azure SQL Database, choose its card and select Continue to configure.
Copy the Azure SQL server hostname and database name, and prepare a SQL-authentication user and password.
GateRook’s SQL Server connector uses SQL authentication. Microsoft Entra and Windows sign-in are not available in this form.
Enter a Name, for example azure-sql-demo. Your AI app uses this name to choose the connection.
Choose Azure SQL Database. Enter a Name, the fully qualified server Host, Port 1433, and the SQL User and Password.
Keep SSL mode at verify-full. Use the server hostname rather than an IP so the TLS identity can be checked.
Select Load databases and choose the intended database. Check Default schema, normally dbo, and use Schema allowlist to narrow access further.
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.
If the connection times out, check Azure SQL firewall or private-endpoint access. If login or database loading fails, check the SQL login’s database access and whether the account depends on unsupported Entra sign-in.
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 Azure SQL Database on the endpoint and passing its connection test, ask your AI app to use azure-sql-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 in my Azure SQL Database connection.”
- “Describe the columns and keys of the selected Azure SQL table.”
- “Show the five most recent orders in my Azure SQL database.”
| 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.