An AI assistant can help investigate a subscription problem, explain an unfamiliar schema, or calculate revenue by plan. Those tasks rarely require a customer's name, email address, phone number, date of birth, or home address.

Yet a perfectly ordinary SQL query can return all of them. Once the tool response reaches the AI client, those values may enter the model's context, the conversation history, or another downstream system. Asking the assistant to leave personal details out of its final answer happens too late: it has already received them.

This walkthrough puts GateRook between the AI app and PostgreSQL . We will let the assistant query a small customer database while GateRook replaces selected personal data with ‹masked› before returning the result. Then we will run useful analysis over the remaining data and inspect the actual AI call in Activity.

Disclosure: I build GateRook , an open-source desktop MCP Firewall. Its application source is on GitHub .…