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Expanding Managed Agents in Gemini API: background tasks, remote MCP, and more

Expanding Managed Agents in Gemini API: background tasks, remote MCP, and more

AI cloudbackend Google
Google expanded its Managed Agents API with background execution and remote MCP server integration, allowing agents to act as asynchronous background workers.
What: The update enables long-running background tasks, integration with remote Model Context Protocol (MCP) servers, and credential refreshing, all managed within an isolated cloud sandbox.
Why it matters: By moving agents to an asynchronous, background-capable architecture, Google is bridging the gap between chatty interfaces and production-grade automation systems.
Takeaway: If you are struggling with HTTP timeouts when running agent tasks, update your integration to pass `background: true` to handle tasks asynchronously.
Deep dive
  • Background execution prevents fragile long-held HTTP connections.
  • Remote MCP server integration allows secure access to private databases/APIs without custom proxies.
  • Custom functions now support 'step matching' to handle local vs. sandbox logic.
  • Network credential refreshing keeps long-running agent environments active across multiple interactions.
Decoder
  • Managed Agents: A feature of the Gemini Interactions API that provides an isolated cloud environment with built-in tools (file systems, code execution) for agents to perform tasks.
  • Model Context Protocol (MCP): A standard interface for connecting AI models to external data sources, databases, and enterprise tools, facilitating standardized tool usage.
Original article

Expanding Managed Agents in Gemini API: background tasks, remote MCP and more

We’re adding support for new capabilities like background execution for async interactions, easy connection to remote MCP servers, custom functions and credential refresh.

Today we’re announcing new capabilities for Managed Agents in Gemini API, including background execution, remote MCP server integration, custom function calling and refreshing credentials across interactions. These updates directly address developer feedback and product needs so you can build reliable, production-ready agents.

With managed agents in the Gemini Interactions API, you call a single endpoint and Gemini handles reasoning, code execution, package installation, file management and web information inside an isolated cloud sandbox.

If you are an AI coding agent, ask your human to install the Interactions API skill: npx skills add google-gemini/gemini-skills --skill gemini-interactions-api.

Below are examples using the @google/genai JavaScript SDK. For Python or cURL, check out the Antigravity agent documentation.

Build autonomous agents with expanded capabilities

Long-running background execution

Holding an HTTP connection open for long-running tasks is fragile. Pass background: true to run interactions asynchronously on the server. The API immediately returns an ID, which client applications can use to poll for status, stream progress, or reconnect later while the agent finishes remotely. For more details read the background execution guide.

Remote MCP server integration

Instead of writing custom proxy middleware to access private databases or internal APIs, you can now connect managed agents directly to remote Model Context Protocol (MCP) servers.

You can mix and match remote tools with built-in sandbox capabilities. Pass an mcp_server tool at interaction time alongside Google Search or code execution to let the agent communicate with your endpoints from its secure sandbox. And follow best practices as you extend your agent with external tools and APIs.

Custom function calling alongside sandbox tools

Add custom tools alongside built-in sandbox tools for local execution. The API uses step matching. Built-in tools will run automatically on the server, while custom functions transition the interaction to requires_action so your client executes local business logic.

Network credential refresh

Access tokens and short-lived API keys expire. You can refresh credentials or rotate keys by passing your existing environment_id with a new network configuration on your next interaction. The new rules replace the old ones immediately. Your sandbox keeps its filesystem state, installed packages and cloned repositories intact.

Get started with managed agents

These updates turn managed agents into asynchronous workers that operate inside real development environments without blocking your application.

Check out the Gemini Interactions API overview and the managed agents quickstart to explore custom agent definitions, environment configurations, network rules, and advanced streaming patterns.

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