Getting started with AI Governance on Databricks

As AI agents move from prototypes to production, a new architectural layer is emerging: the tool gateway. Models alone aren't enough — agents need secure, real-time access to data, APIs, and enterprise systems. Integrating these tools consistently and safely has become one of the biggest bottlenecks to adoption.In this session, we explore how Model Context Protocol (MCP) and tool gateways redefine how agents interact with the world. MCP standardizes how agents discover and use tools dynamically, while AI Gateway acts as the enterprise control plane to govern access, manage credentials, and monitor usage across every tool and model. Together, they replace fragmented APIs with a unified, governed interface — letting agents securely connect to managed, external, and custom MCP servers and select tools at runtime.Through real architectures, you'll see how to design agent systems that are flexible, interoperable, and production-ready across internal data and third-party systems.