Google Gemini just gave developers much stronger tools for production AI agents.

i.e. Gemini API Managed Agents now are much closer to production with new addition of background tasks, remote MCP, function calls, credential refresh, and free-tier access.

Managed Agents are Google-hosted AI workers that run antigravity-preview-05-2026 inside an isolated Linux sandbox.

Older agent apps often broke when a long task outlived a normal HTTP request.

An "Interaction" is the important object here. It stores the task, the model’s steps, tool calls, tool results, and final output.

So instead of your app manually tracking every turn, tool result, and file, Google tracks much of that server-side.

Remote MCP support changes the tool story, because agents can contact private services without custom proxy glue.

A company can now connect observability, databases, or internal APIs beside Google Search and code execution.

Function calling adds another split, where Google runs sandbox tools and your app handles business logic.

Credential refresh fixes a production pain, since short-lived tokens can rotate without losing sandbox state.

Overall, this makes Gemini API feel less like a model endpoint and more like agent infrastructure.