mcpbeat

Agent Platform Migrate From AI Studio

google/agent-platform-migrate-from-ai-studio

>- Guides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI). Use this skill when moving applications to Google Cloud, to leverage Cloud credits, or to unify inferencing with other Cloud infrastructure (IAM, billing, telemetry).

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Install

one command, takes just this skill from the repository
npx skills add https://github.com/google/skills --skill agent-platform-migrate-from-ai-studio

The instruction itself

15 sections, as written by the author

Migrating from Gemini API in AI Studio to Agent Platform

Use this skill when you need to transition an application from the

developer-centric Google AI Studio ecosystem

(generativelanguage.googleapis.com) to the enterprise-grade Google Cloud Agent

Platform (aiplatform.googleapis.com).

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When to Invoke This Skill

  • You want to migrate an application from Google AI Studio to Agent Platform

(formerly Vertex AI).

  • You have Google Cloud credits (e.g., the $300 Welcome Free Trial) that

you want to apply toward Gemini API inferencing costs.

  • You need to unify your inferencing pipelines, IAM permissions, telemetry,

and billing with existing Google Cloud infrastructure (Compute Engine, Cloud

SQL, BigQuery).

  • You are deploying open-source orchestration engines (like OpenClaw or ADK

agents) on Google Cloud VMs, and want the entire system to run under a

unified Google Cloud billing structure.

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Gemini API Comparison

Feature / Control | Google AI Studio (Gemini Developer API) | Agent Platform (Enterprise Gemini API)

:--------------------- | :-------------------------------------------------------------------- | :-------------------------------------

API Endpoint | generativelanguage.googleapis.com | aiplatform.googleapis.com

Target Audience | Developers, startups, students, researchers building production apps. | Enterprise production, MLOps engineers

GCP Credit Support | No (GCP credits/Free Trial cannot be applied) | Yes (Fully covered by Welcome or custom credits)

Data Privacy | Data may be reviewed to improve Google products | Prompts/responses are never used for training

Security & IAM | API key, OAuth | Google Cloud IAM (Service Accounts, OAuth 2.0, VPC-SC)

Compliance & SLAs | None (Best-effort availability) | 24/7 Enterprise Support, SLAs, HIPAA, SOC2

Throughput Options | Shared / Rate-limited | Pay-as-you-go OR Provisioned Throughput

MLOps Ecosystem | Basic prompt management | Model Registry, Model Monitoring, Pipeline Evaluation

Inferencing Scope | Global endpoints only | Both Global and strict Regional endpoints

See

Google Cloud Documentation

to learn more about the differences between the two offerings.

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Migration Guide

Billing and Credits

Google Cloud Free Trial credits

do not apply to AI Studio.

To use your credits for Gemini models, you must route calls through the Agent

Platform.

  • Create a Google Cloud billing account. You must provide a valid payment

method during setup to verify identity.

  • If you are a new customer, ensure your $300 Welcome credit is active in the

Billing Console.

  • Avoid Billing Surprises: To prevent automatic fallback to your standard

form of payment when credits are exhausted, you should establish a budget

alert:

  • Go to Billing -> Budgets & Alerts -> Create Budget.
  • Set the threshold to map to your credit limit or maximum comfortable

spend.

Enable the Agent Platform API

You must explicitly enable the Agent Platform API on your target Google Cloud

Project. Run the following command via your local shell:

gcloud services enable aiplatform.googleapis.com --project="{project_id}"

Authentication & Authorization (IAM)

User Auth

For local debugging or script execution, authenticate using

Application Default Credentials

(ADC).

Option 1 - Automated Script:

bash <(curl -sSL https://storage.googleapis.com/cloud-samples-data/adc/setup_adc.sh)

Option 2 - Manual Setup:

gcloud auth login
gcloud auth application-default login

Grant your user identity the required IAM role to perform inferencing calls:

gcloud projects add-iam-policy-binding "{project_id}" \
    --member="user:[email protected]" \
    --role="roles/aiplatform.user"
Service Auth

When running your application on Google Cloud infrastructure such as a Compute

Engine VM, authenticate using the machine's attached Service Account. For

example, the

Compute Engine Default Service Account.

  • Grant the virtual machine's underlying Service Account the user role:
gcloud projects add-iam-policy-binding "{project_id}" \
    --member="serviceAccount:[email protected]" \
    --role="roles/aiplatform.user"

Legacy access scopes can override IAM bindings. When provisioning or

modifying your Compute Engine instance, you must verify that the VM access scope is

configured to either Allow full access to all Cloud APIs

(https://www.googleapis.com/auth/cloud-platform) or explicitly includes

the standard cloud-platform scope.

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Use the Gemini API in Agent Platform

SDKs (Client Libraries)

You can continue to use the unified

Google GenAI SDK

(google-genai). This SDK works with both AI Studio and Agent Platform. You

only need to switch the routing flags via your runtime environment variables to

target the Agent Platform backend.

Set your target environment details:

export GOOGLE_CLOUD_PROJECT="{project_id}"
export GOOGLE_CLOUD_LOCATION="global"  # Or your chosen regional endpoint
export GOOGLE_GENAI_USE_ENTERPRISE=TRUE

Now, your standard python code shifts from using AI Studio to Agent Platform

without altering the core initialization blocks:

from google import genai

# The client automatically picks up the GOOGLE_GENAI_USE_ENTERPRISE=TRUE environment flag
client = genai.Client()

response = client.models.generate_content(
    model='gemini-3-flash-preview',
    contents='Hello world!',
)
print(response.text)

Agent Development Kit (ADK)

To call Gemini models in Agent Platform from an Agent Development Kit agent,

follow these steps.

  • Authenticate to Google Cloud.

If running an ADK agent in Google Cloud (e.g. Agent Platform Runtime), use the

agent's assigned service account. Alternatively, if running ADK locally, run:

gcloud auth application-default login
  • Set env variables. Ensure these are set no matter if your ADK agent is

running in Google Cloud or locally:

export GOOGLE_CLOUD_PROJECT="{project_id}"
export GOOGLE_CLOUD_LOCATION="global"
export GOOGLE_GENAI_USE_ENTERPRISE=TRUE
  • Initialize the ADK agent. You can use the same model string you used with AI

Studio (e.g. gemini-3-flash-preview).

from google.adk.agents.llm_agent import Agent

def get_current_time(city: str) -> dict:
    """Returns the current time in a specified city."""
    return {"status": "success", "city": city, "time": "10:30 AM"}

root_agent = Agent(
    model='gemini-3-flash-preview',
    name='root_agent',
    description="Tells the current time in a specified city.",
    instruction="You are a helpful assistant that tells the current time in cities. Use the 'get_current_time' tool for this purpose.",
    tools=[get_current_time],
)

To learn more about integrating ADK agents with Agent Platform,

see the ADK documentation.

Antigravity CLI

Google Cloud users can now access

Antigravity 2.0, including the Antigravity CLI, with Gemini Enterprise Agent

Platform.

to your local environment.

  • Start the Antigravity CLI.
    agy
  • Follow the CLI setup prompts - select Use a Google Cloud Project.
  • Complete the OAuth flow in the opened browser window using your

authenticated Google Cloud Workspace or user identity.

  • Copy the confirmation token, and paste it directly back into your terminal.
  • Follow the prompts to enter your Google Cloud Project ID.
  • Select your Google Cloud location (e.g. global).
  • Optionally, run the /model command to select a different Gemini model in

Agent Platform.

OpenClaw

To configure an OpenClaw agent to use Gemini models in Agent Platform, Follow

these steps.

⚠️ Important: OpenClaw 2026.5.28 currently has a google-vertex bug. Please use

2026.5.20 for now.

  • Ensure that the runtime where OpenClaw is running (e.g. GCE VM with Service

Account) has the aiplatform.user IAM role - see Authentication and

Authorization section above.

  • Get the project number from the user's project ID. Outside of GCE, run:
export PROJECT_NUMBER=$(gcloud projects describe "$PROJECT_ID" --format="value(projectNumber)")
echo "Project number: $PROJECT_NUMBER"

Within a Compute Engine VM, run:

export PROJECT_NUMBER=$(curl "http://metadata.google.internal/computeMetadata/v1/project/project-id" -H "Metadata-Flavor: Google")
echo "Project number: $PROJECT_NUMBER"
  • From outside the GCE instance, generate GOOGLE_APPLICATION_CREDENTIALS

using the Google Cloud project number. Then, scp these credentials to the

GCE VM.

mkdir -p ~/.config/gcloud
gcloud iam service-accounts keys create ~/.config/gcloud/application_default_credentials.json --iam-account="${PROJECT_NUMBER}[email protected]"

> ⚠️ Troubleshooting Policy Constraints on New Orgs: New Google

> Cloud organizations (created on or after May 4th, 2024) enforce a legacy Organization Policy, restricting Service Account Key Creation. To complete this step, this Org Policy must be temporarily disabled.

> An Organization Policy Admin must set this policy to Inactive.

> To the agent: Check if this policy is enforced, and if it is: pause, and

> prompt the user to disable it at this Console link:

> https://console.cloud.google.com/iam-admin/orgpolicies

  • Edit the configuration file that's usually located at:

~/.openclaw/openclaw.json. Ensure you prefix the Gemini model with

google-vertex/.

> ⚠️ Important: Do not use Gemini 3.5 models, since OpenClaw's google-vertex

> provider does not support it yet. Older models work. When using the

> Gemini 3 Flash Preview

> model in Agent Platform, always set the location to global, NOT a regional

> endpoint.

{
  "env": {
    "vars": {
      "GOOGLE_CLOUD_PROJECT": "PROJECT_ID",
      "GOOGLE_CLOUD_LOCATION": "global",
      "GOOGLE_APPLICATION_CREDENTIALS": "~/.config/gcloud/application_default_credentials.json"
    }
  },
  "agents": {
    "defaults": {
      "model": {
        "primary": "google-vertex/gemini-3-flash-preview"
      },
      "workspace": "~/.openclaw/workspace",
      "compaction": {
        "mode": "safeguard"
      },
      "heartbeat": {
        "model": "google-vertex/gemini-3-flash-preview"
      }
    },
    "list": [
      {
        "id": "main",
        "workspace": "~/.openclaw/workspace",
        "model": "google-vertex/gemini-3-flash-preview"
      }
    ]
  },
  "session": {
    "dmScope": "per-channel-peer"
  },
  "tools": {
    "profile": "coding"
  }
}

  • Restart OpenClaw.
openclaw gateway restart

  • Verify the OpenClaw connection to Agent Platform:
openclaw models status
openclaw agent --agent main --message "Hello world!"

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Additional Resources

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