Stefania Leone

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.

Do you have users that wear multiple hats over a day? Like working with data from various customers and hoping they don’t inadvertently aggregate data? Or are they working on sensitive datasets such as clinical trials that should not be combined, or are data sets that are subject to regulations? We have a solution! In this session, we will present a new capability that allows users wearing multiple hats to switch roles in the Databricks workspace to work exclusively on a dedicated project, data of a particular client or clinical trial. When switching to a particular role, the workspace adapts in such a way that only workspace objects and UC data of that particular role are accessible. We will also showcase the administrative experience of setting up exclusive access using groups and UC permissions.