A SQLite database file on this computer. Read queries and schema.
The screenshots show GateRook 2.0.0: the SQLite 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 SQLite, choose its card and select Continue to configure.
Have an existing SQLite database file on the computer running GateRook. This connection reads the file directly; it does not connect to a database server or create a new file.
Choose a database you are allowed to inspect. Reads use a read-only handle; an approved change needs filesystem write permission and can affect the application that owns the database.
Enter a Name, for example sqlite-demo. Your AI app uses this name to choose the connection.
In Database file, choose the existing file or enter its path, for example ~/projects/shop/db/development.sqlite3. You must choose the file yourself.
Under Advanced, review Lock wait if another application writes to the file. Keep Enforce foreign keys enabled when the database relies on foreign-key constraints.
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 test reports a missing or unreadable file, check the path and your operating-system permissions. A lock error means another program may be holding the database; wait for its transaction to finish and test again.
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 SQLite on the endpoint and passing its connection test, ask your AI app to use sqlite-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.
For this local-file connection, file permissions and configured path restrictions determine which data can be read or changed.
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 and views in sqlite-demo.”
- “Describe the columns and keys of the orders table in sqlite-demo.”
- “Using sqlite-demo, count orders by status without changing the database.”
| Tool | What it does | Starts as |
|---|---|---|
sql_list_schemas | List tables and views in the selected local SQLite database file, within the connection and policy restrictions. | Read only |
sql_describe_table | Describe a SQLite table’s columns, types, keys and indexes where available. | Read only |
sql_query | Run one validated SQLite read statement using a read-only file connection, then roll back. Connection and endpoint limits still apply. | Read only |
sql_execute | Run one supported data or schema change with Approval by default, using a separate writable connection. File permissions and the environment policy still apply. | Approval |
You can change each tool’s mode on the endpoint. Every call your AI makes appears in Activity.