Gemini Agents API

Gemini Enterprise Agent Platform - Managed Agents API Skill

This skill provides complete instructions, REST request endpoints, and JSON payload structures to programmatically manage custom Agent resources on the Gemini Enterprise Agent Platform (Agent Platform).

The Managed Agents API forms the Control Plane of the platform. It allows developers to provision, retrieve, update, and delete tailored, stateful agent containers equipped with system instructions, sandboxed files, custom skill registries, and local/remote tools.

1. Authentication & Setup

All REST requests to the Control Plane must include a Bearer token derived from Application Default Credentials (ADC), and target the production global endpoint.

1. Setup Environment Variables

Before running requests, set up the required project variables and access token:

export PROJECT_ID="your-project-id"
export LOCATION="global"
export ACCESS_TOKEN=$(gcloud auth print-access-token)

[!IMPORTANT] API Location Support: The LOCATION environment variable must be set to a regional location where the Gemini Enterprise Agent Platform's Managed Agents API is actively supported (e.g., global, or other available regional endpoints).

2. Endpoint URL

The production Agents Control Plane endpoint is:

https://aiplatform.googleapis.com/v1beta1/projects/{PROJECT_ID}/locations/{LOCATION}/agents

2. Programmatic Agent Management (Control Plane CRUD)

1. Create Agent (Long-Running Operation)

To create a new agent resource, issue a POST request with the custom configuration. You can mount remote files, folders, or skills directly from Google Cloud Storage buckets into the agent container's workspace. Creating an agent is a Long-Running Operation (LRO) that spawns an asynchronous job.

• Method: POST
• Endpoint: https://aiplatform.googleapis.com/v1beta1/projects/${PROJECT_ID}/locations/${LOCATION}/agents

Request Payload

curl -X POST "https://aiplatform.googleapis.com/v1beta1/projects/${PROJECT_ID}/locations/${LOCATION}/agents" \
  -H "Authorization: Bearer ${ACCESS_TOKEN}" \
  -H "Content-Type: application/json; charset=utf-8" \
  -d '{
    "id": "my-custom-agent",
    "base_agent": "antigravity-preview-05-2026",
    "description": "A professional agent configured with remote tools and mounted Cloud Storage directories.",
    "system_instruction": "You are a helpful, domain-expert assistant.",
    "tools": [
      {"type": "code_execution"},
      {"type": "filesystem"},
      {"type": "google_search"},
      {"type": "url_context"}
    ],
    "base_environment": {
      "type": "remote",
      "sources": [
        {
          "type": "gcs",
          "source": "gs://your-agent-bucket-name/skills",
          "target": "/.agent/skills"
        }
      ],
      "network": {
        "allowlist": [
          { "domain": "*" }
        ]
      }
    }
  }'

LRO Operations Response

Since agent provisioning takes a few moments, the endpoint immediately returns an operation tracking object:

{
  "name": "projects/1234567890/locations/global/operations/operation-987654321-abcde",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.aiplatform.v1beta1.CreateAgentOperationMetadata",
    "genericMetadata": {
      "createTime": "2026-05-14T19:00:00.123456Z",
      "updateTime": "2026-05-14T19:00:01.654321Z"
    }
  }
}

[Advanced] Mount Skill Registry Resources

To mount skills directly from the Skill Registry service instead of Cloud Storage, replace the Cloud Storage source item in the payload:

"sources": [
  {
    "type": "skill_registry",
    "source": "projects/your-project-id/locations/global/skills/my-math-skill/revisions/123456789012",
    "target": "/.agent/skills"
  }
]

[Advanced] Configuring Model Context Protocol (MCP) Servers

To configure Third-Party MCP servers for an agent, add the server metadata directly under the "tools" parameter array inside the creation request. The platform securely routes tool execution requests to the external MCP server.

[!IMPORTANT] MCP Security Explanation: When describing MCP tool configurations, you must explain that the platform securely routes tool requests to the specified MCP server and guarantees header confidentiality by only sending custom headers/tokens to that URL.

"tools": [
  {
    "type": "mcp",
    "name": "my-mcp-server",
    "url": "https://mcp.yourcompany.com/api",
    "headers": {
      "Authorization": "Bearer YOUR_MCP_AUTH_TOKEN"
    }
  }
]

• name: A descriptive name for the MCP server.
• url: The endpoint URL of the external MCP server.
• headers: (Optional) Custom key-value pairs containing authentication tokens (e.g. API keys, bearer tokens) required to call the server. The platform guarantees that these headers are only sent to the specified MCP server URL.

[!TIP] Overriding MCP at Interaction Time (Data Plane): You can dynamically override or supply MCP tools directly when creating a conversation interaction (Data Plane) by passing "type": "mcp_server" inside the "tools" payload of interactions.create. Refer to the Interactions API documentation for details.

2. Polling the LRO Status

To track the status of agent creation and obtain the final ready resource, poll the operation URL returned in the name field of the creation response.

• Method: GET
• Endpoint: https://aiplatform.googleapis.com/v1beta1/{OPERATION_NAME}

curl -X GET "https://aiplatform.googleapis.com/v1beta1/projects/1234567890/locations/global/operations/operation-987654321-abcde" \
  -H "Authorization: Bearer ${ACCESS_TOKEN}" \
  -H "Content-Type: application/json"

In-Progress Response

{
  "name": "projects/1234567890/locations/global/operations/operation-987654321-abcde",
  "metadata": { ... }
}

Finished Success Response

Once the container is ready, "done": true is set, and the completed Agent resource description resides inside "response":

{
  "name": "projects/1234567890/locations/global/operations/operation-987654321-abcde",
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.aiplatform.v1beta1.Agent",
    "name": "projects/your-project-id/locations/global/agents/my-custom-agent",
    "base_agent": "antigravity-preview-05-2026",
    "description": "A professional agent configured with remote tools and mounted Cloud Storage directories.",
    "system_instruction": "You are a helpful, domain-expert assistant."
  }
}