Google Deepmind adds background execution and MCP support to Gemini API agents

Google Deepmind's expansion of the Gemini API's Managed Agents addresses practical bottlenecks in agent deployment. The Background Execution feature removes a technical constraint—the requirement to maintain an open HTTP connection—that would have otherwise forced developers to keep resources allocated for the duration of an agent's work. This is particularly valuable for long-running tasks where maintaining an active connection would be inefficient.

The addition of remote MCP (Model Context Protocol) support signals a strategic move toward interoperability with existing enterprise systems. MCP is an emerging standard for connecting AI systems to external tools and data sources; by allowing agents to connect directly to internal databases and APIs through MCP, Google is positioning Gemini agents as components that can integrate into mature software stacks without heavy custom middleware. The ability to refresh credentials between interactions without resetting sandbox state preserves security and statefulness—two concerns that can otherwise force developers to choose between convenience and safety.

Together, these changes lower friction for developers building production agent applications, particularly those working within organizations with existing database and API infrastructure that they want agents to access safely and persistently.