Deploy an AI Agent to Google Cloud with Google Agents CLI v1.0 (GA)

Building an AI agent is one thing. Getting it into production — containerized, evaluated, CI/CD’d, and running on scalable infrastructure — is a whole other problem. Google just made that second part significantly easier with Agents CLI v1.0, which reached General Availability on July 1, 2026.

This guide walks through what Agents CLI does, how the v1.0 workflow is structured, and how to use it to go from a scaffolded agent project to a deployed Cloud Run service. All commands and configuration patterns described below are sourced from the official Google Agents CLI documentation and GitHub repository.

What Is Google Agents CLI?

Agents CLI is an open-source tool from Google that turns any AI coding assistant (Gemini CLI, Claude Code, Cursor, Codex) into an expert at the full AI agent development lifecycle. It works as a set of “skills” injected into your coding agent, giving it deep knowledge of:

• Scaffolding agent projects from templates
• Evaluating agent behavior with ADK (Agent Development Kit) evaluation harnesses
• Deploying to Google Cloud — Agent Runtime, Cloud Run, or GKE
• Setting up IaC (Terraform) and CI/CD pipelines

Rather than juggling the Gemini CLI, the ADK CLI, gcloud, and Terraform separately, Agents CLI unifies the workflow into a coherent set of commands your coding agent can execute on your behalf.

The project is part of Google’s Gemini Enterprise Agent Platform and is available on GitHub at google/agents-cli.

Prerequisites

Before using Agents CLI, you’ll need:

• A Google Cloud project with billing enabled
• The gcloud CLI installed and authenticated
• Your preferred coding agent (Gemini CLI, Claude Code, or Cursor)
• Python 3.11+ (for ADK-based agents)
• Docker (for containerized deployments)

Installing Agents CLI

⚠️ Note: For the most current installation instructions, always check the official README and the deployment guide. The following reflects the approach documented at the time of the v1.0 GA release.

Based on the official documentation, Agents CLI is installed as a skill into your coding agent using uvx:

uvx google-agents-cli setup

This injects the Agents CLI skill set into your configured coding agent, making all agents-cli commands available within that agent’s context. After setup, your coding agent will have access to the full scaffolding, evaluation, and deployment workflow.

The Three-Phase Workflow

Google Agents CLI organizes agent development into three phases:

Phase 1: Scaffold

Create a new agent project from a template:

# Within your coding agent, after Agents CLI setup:
agents-cli create --name my-agent --template adk-python

This generates a project structure with:

• Agent source code with ADK-compatible patterns
• An agents-cli-manifest.yaml describing your deployment configuration
• Evaluation harness setup
• Basic IaC scaffolding

Phase 2: Evaluate

Before deploying to production, run ADK evaluation harnesses to verify your agent’s behavior:

agents-cli evaluate

The evaluation framework runs your agent against a configured test suite and reports on response quality, tool call accuracy, and task completion rates. This is the key quality gate before any deployment.

Phase 3: Deploy

Once evaluation passes, deploy to your target environment. For Cloud Run deployments:

agents-cli deploy

This reads your agents-cli-manifest.yaml, containerizes your agent, pushes to Artifact Registry, and deploys to Cloud Run (or Agent Runtime, depending on your manifest configuration).

For deployments targeting Agent Runtime (Google’s managed agent hosting), the underlying ADK deploy command is:

uv run adk deploy agent_engine AGENT_NAME \
  --project="YOUR_PROJECT_ID" \
  --region="YOUR_REGION"

(This command is sourced from the official ADK documentation at adk.dev/deploy/agent-runtime/agents-cli/)

Deployment Targets

Agents CLI supports three deployment targets as of v1.0:

The deployment target is configured in your agents-cli-manifest.yaml. The CLI handles all the containerization, registry push, and IaC generation automatically based on this configuration.

Integration with Coding Agents

One of the most interesting aspects of Agents CLI is how it’s designed to work through your coding agent rather than alongside it. When you’re using Claude Code or Cursor, you can ask your coding agent to:

“Use Agents CLI to create a new ADK agent project, evaluate it, and deploy it to Cloud Run”

The coding agent understands the full workflow and can execute the multi-step process — scaffold, configure, evaluate, iterate, deploy — in a single conversational session.

This is what Google means by “skills injected into any coding agent”: Agents CLI doesn’t replace your agent; it gives it new capabilities.

CI/CD Setup

For production deployments, Agents CLI can also scaffold your CI/CD pipeline:

agents-cli setup-cicd --platform github-actions

This generates a GitHub Actions workflow that runs evaluation on every pull request and automatically deploys to your target environment on merge to main.

(Verify the exact flag names and platform options in the official deployment guide before using this command in production)

Getting Started

The fastest path to your first deployment:

1. Install: uvx google-agents-cli setup in your coding agent
2. Scaffold: Ask your coding agent to create a new project with agents-cli create
3. Iterate locally: Build and test your agent logic
4. Evaluate: Run agents-cli evaluate and review results
5. Deploy: Run agents-cli deploy and watch your agent go live

The official Getting Started guide at google.github.io/agents-cli is the best reference for the complete setup walkthrough.

Sources

1. google/agents-cli — GitHub (Apache-2.0)
2. Google Developers Blog — Agents CLI in Agent Platform
3. Official Deployment Guide
4. ADK Agent Runtime Deployment Docs
5. Google Cloud Agent Platform Docs

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260704-2000

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