Agent Registry can register agents hosted on supported Google Cloud runtimes without requiring you to manually call the Agent Registry API. Depending on the runtime, this registration process happens automatically or requires an opt-in configuration step during deployment. This document explains how to enable discovery for agents on supported runtimes. If you host an agent externally or on an unsupported runtime, see [Use manual registration](https://docs.cloud.google.com/agent-registry/manual-registration). The metadata and [A2A skills](https://docs.cloud.google.com/agent-registry/concepts#a2a-skill) extracted from an agent during its registration depend on the agent's protocol. For more information, see [Register agents](https://docs.cloud.google.com/agent-registry/register-agents). ## Before you begin Before you register agents, [set up Agent Registry](https://docs.cloud.google.com/agent-registry/setup). You need [your project ID](https://support.google.com/googleapi/answer/7014113) to verify registration. To use the Google Cloud CLI commands in this document, make sure you have [set up your gcloud CLI environment](https://docs.cloud.google.com/agent-registry/setup#set-up-cli). ## Register agents from Agent Runtime If you develop and deploy agents with [Agent Runtime on Gemini Enterprise Agent Platform](https://docs.cloud.google.com/gemini-enterprise-agent-platform/build/runtime), registration in Agent Registry is automatic. The [Agent2Agent (A2A) protocol](https://a2a-protocol.org/latest/) is an open standard that lets agents declare their capabilities and identity. The following example shows how to deploy an [agent implementing the A2A protocol](https://docs.cloud.google.com/agent-registry/register-agents#automatic-registration) to Agent Runtime. For more information, see [Deploy an agent](https://docs.cloud.google.com/gemini-enterprise-agent-platform/scale/runtime/deploy-an-agent). # Create and deploy the agent # This action automatically registers the agent in Agent Registry remote_agent = client.agent_engines.create( agent=my_a2a_agent, # Your defined A2A object config={ "display_name": "my-support-agent", "description": "An agent that handles support tickets.", "requirements": ["google-cloud-aiplatform[agent_engines,langchain]"], }, ) As you update or delete your agent in Agent Runtime, Agent Registry automatically synchronizes those changes. ## Register built-in Google agents Built-in Google agents, such as [Google Workspace](https://developers.google.com/workspace/guides/get-started) and [Gemini Enterprise](https://docs.cloud.google.com/gemini/enterprise/docs) agents, are automatically registered in Agent Registry. You don't need to perform any configuration or deployment steps. These agents are ingested and available for [discovery](https://docs.cloud.google.com/agent-registry/concepts#discovery) within your registry. ## Register agents from GKE You can register agents deployed on [Google Kubernetes Engine (GKE)](https://docs.cloud.google.com/kubernetes-engine/docs/tutorials/agentic-adk-vertex) by adding the `registry.gke.io/functional-type: "AGENT"` label to your deployments. This label identifies the deployment as an AI agent, letting Agent Registry perform an introspection scan. > [!NOTE] > **Note:** GKE also supports the `apphub.cloud.google.com/functional-type: "AGENT"` annotation for backward compatibility. However, we recommend using the `registry.gke.io/functional-type: "AGENT"` label for your GKE deployments. To enable automated discovery of the agent's skills, you must also provide the `a2a-protocol.org/agent-card` annotation. The ingestion controller uses this annotation to query the A2A Agent Card. The following example shows a GKE agent deployment manifest using these configurations. For more information, see [Deploy and orchestrate AI agents](https://docs.cloud.google.com/kubernetes-engine/docs/tutorials/agentic-adk-vertex). apiVersion: apps/v1 kind: Deployment metadata: name: my-agent labels: # GKE takes this label and registers the agent to Agent Registry registry.gke.io/functional-type: "AGENT" annotations: # A2A protocol metadata annotation for automated Agent Card discovery a2a-protocol.org/agent-card: | card: endpoint: /.well-known/agent-card.json protocol: HTTP port: 8080 spec: selector: matchLabels: app: my-agent template: metadata: labels: app: my-agent spec: containers: - name: server image: gcr.io/my-project/my-agent:1.0.0 ports: - containerPort: 8080 env: - name: PORT value: "8080" --- apiVersion: v1 kind: Service metadata: name: my-agent-service labels: app: my-agent spec: type: ClusterIP ports: - port: 8080 targetPort: 8080 protocol: TCP name: http selector: app: my-agent When the deployment is applied, the GKE cluster automatically attempts to fetch metadata from the agent and syncs it directly into the Agent Registry data model. ## Verify registration You can verify that Agent Registry successfully registered your agents by listing them: ### Console 1. In the Google Cloud console, go to **Agent Registry**: [Go to Agent Registry](https://console.cloud.google.com/agent-platform/agent-registry)
2. From the project picker, select the Google Cloud project where you [set up Agent Registry](https://docs.cloud.google.com/agent-registry/setup). 3. Select the **Agents** tab. The page displays a list of all registered agents and their details, such as name, [identifier](https://docs.cloud.google.com/agent-registry/concepts#agent-identifier), description, runtime, and location. 4. Filter the list by the agent's location or its runtime resource: - To filter by location, click the **Location** menu, select the locations you want to filter, and click **Apply**. - To filter by runtime, click the **Runtime** menu, select the runtimes you want to filter, and click **Apply**. The page displays a filtered list of the registered agents for your selected conditions. ### gcloud You can filter the list by the agent's metadata. Make sure you have [set up your Google Cloud CLI environment](https://docs.cloud.google.com/agent-registry/setup#set-up-cli) for Agent Registry, and then run: gcloud agent-registry agents list \ --project=PROJECT_ID \ --location=REGION \ --filter="FILTER_EXPRESSION" Replace the following: - `PROJECT_ID`: The project ID. - `REGION`: The registry region. - `FILTER_EXPRESSION`: The filter expression for the agents that you want to filter. For example, to filter by display name, you can use `displayName='DISPLAY_NAME'`. To filter by the globally unique [identifier](https://docs.cloud.google.com/agent-registry/concepts#agent-identifier) (URN), you can use `agentId='urn:agent:AGENT_URN'`. Built-in Google agents use a URN format that depends on where the agent is deployed. For example, you can discover built-in Google Workspace agents by filtering your list for the `googleapis.com` publisher using `--filter="agentId:'urn:agent:googleapis.com:*'"`. ### Terraform Reference your registered agent in other Terraform configurations by using the `google_agent_registry_agent` data source: data "google_agent_registry_agent" "my_agent" { location = "REGION" filter = "displayName=\"DISPLAY_NAME\"" } output "agent_urn" { value = data.google_agent_registry_agent.my_agent.urn } Replace the following: - `REGION`: The registry region. - `DISPLAY_NAME`: The human-readable display name of the agent.