Use Supabase with an AI coding agent by defining your data model, identity flows, authorization rules, and environments before asking it to integrate the service. Give the agent the exact project stack and current Supabase documentation that matches your setup, since product interfaces can change.
Start with one entity and one user journey. Describe fields, relationships, ownership, allowed actions, and deletion behavior. If the workflow uses Supabase’s MCP server, scope it to the intended project, select only the needed tool groups, and use read-only SQL mode where appropriate; still review interactive tool calls and keep the first trial away from production. Ask the agent to draft schema and migrations, then review them before execution. Keep development and production projects separate, store credentials in managed environment configuration, and grant only the access required for the task. Test database constraints and authorization with at least two identities, including forbidden reads and writes. Inspect generated client and server code to ensure privileged credentials never reach the browser.
Do not use a successful UI demo as proof that the backend is safe. Verify policies at the data boundary, compare migrated records, and capture logs that help diagnose failures without exposing secrets. Confirm any product-specific command or setting against current official docs.
Build a small end-to-end slice and preserve its setup steps, tests, and recovery path. Once access and migration behavior are understood, let the agent extend the same pattern. Supabase’s MCP controls support development workflows; they are not end-user authorization or automatic production approval.
