Second, the Databricks AI Dev Kit Power shipped in the Kiro Powers catalog in PR #129. Open the Powers panel, click Try, and the Power runs the entire onboarding: installer, MCP wiring, auth detection, and skill loading.

Combined with the four Databricks-managed remote MCP servers that already ship inside the platform, you have two ways to wire Kiro into Databricks. Both share a common outcome: builders ship analytics, pipelines, and agent workflows faster when the assistant inherits real workspace permissions instead of guessing at schemas, columns, and grants.

The two milestones above make Kiro × Databricks practical. The reason it matters is what's underneath. Three things make Databricks the substrate of choice for AI-assisted development, regardless of which path you take.

Unity Catalog is the only governance layer that grounds AI at the data level. Every MCP call — Path A or Path B — inherits row, column, and tag-based grants. The assistant doesn't have a privileged view of your data; it sees exactly what you can see. There is no separate access-control layer to manage, and no risk of the AI writing queries against tables it shouldn't even know exist.