Expanding Managed Agents in Gemini API: background tasks, remote MCP and more
We’re announcing new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.
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 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. 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. Add custom tools alongside built-in sandbox tools for local execution.
