Developer’s guide to implementing MCP apps in Gemini

ملخص مفصل

Invokes live APIs, but outputs static text. Every change requires another model turn. Generation 3 (Interactive MCP Apps): Pairs each tool with a live workspace. Adjustments…

Enterprise assistants still respond mostly in text. However, that can break down for visual, multi-step work, where every adjustment costs another slow chat turn.

MCP Apps (SEP-1865) solves this. This open Model Context Protocol (MCP) extension pairs a tool with a live UI. In Gemini Enterprise, that UI renders directly in the chat flow inside a sandboxed iframe, and can expand to fullscreen or a side panel. Edits run locally while the workspace and assistant stay synchronized.

You also avoid rebuilding core foundations: Gemini provides workforce sign-in, governed data access, and the Default Assistant, while you host your MCP server on a private Cloud Run service.

Each tier talks only to its neighbor, letting Gemini Enterprise enforce security and routing.

Each user signs in through OAuth 2.0. On every call, Gemini Enterprise sends its service agent token alongside the user's OAuth token:

Cloud Run IAM cannot distinguish end users, so both layers are required. Outbound calls use a least-privilege service account.

First, build your custom MCP server (exposing POST /mcp and a bundled ui:// HTML widget) using the MCP Apps SDK, or use Google Antigravity to scaffold and deploy your MCP App with this starter prompt:

Once your MCP server code is ready, deploy it to Cloud Run and connect it to Gemini Enterprise:

An MCP App pairs backend tools with a live workspace in Gemini Enterprise. You do not build a chat frontend or identity pipeline; you deploy one Cloud Run container and attach it as a Data Store, making Gemini Enterprise where enterprise work gets done.

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