How to Use the Zentitle2 MCP in Google ADK

Q: How does Zentitle2 help manage client accounts with Google ADK?

You use listcustomers and getcustomerdetails. The agent runs these tools to pull up current account data, which the Gemini model then processes against other enterprise resources in your Google Cloud setup.

Q: What is the process for provisioning entitlements using Zentitle2 with Google ADK?

Your agent calls createentitlement to provision access. It can also check what's already active using listentitlements. This ensures that your Gemini model doesn't hallucinate a required entitlement.

Q: Can I use Zentitle2 with Google ADK for activation code tracking?

Yes. The agent can generate codes via createactivationcode and then list all records using listactivationcodes. This provides a full audit trail that integrates well with Vertex AI.

Act on enterprise license data using Google ADK, connecting Zentitle2 to BigQuery workflows.

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Connect Zentitle2 MCP to Google ADK

Create your Vinkius account to connect Zentitle2 to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Zentitle2 with Google ADK

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Retrieving Customer and Entitlement Records

The `get_customer_details` tool allows your agent to pull specific customer records. Similarly, you can get detailed entitlement information using `get_entitlement_details`. This gives the Gemini model context it needs for complex reasoning. When running on Google Cloud, these tools provide verifiable data points that BigQuery can use for analysis, making the agent's output highly actionable.

Managing Licensing State with MCP Server

Your agent uses `list_entitlements` to see all licensed products and track active rights. It provisions new access using `create_entitlement`, ensuring the necessary records are written back into the ecosystem. This workflow is ideal for building enterprise agents because it doesn't just read data; it actively changes the license state, which you can then model in BigQuery.

Handling Code Generation and Verification

The `create_activation_code` tool lets your agent generate a new code when needed. It also gives visibility into existing codes via `list_activation_codes`. This keeps the entire licensing process in one place. Because of its native connection to Google Cloud, this data flow is perfect for long-context reasoning—the model can hold all these activation details while solving a complex business problem.

Setup guide

Set up Zentitle2 MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Zentitle2 tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Zentitle2_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Zentitle2 tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Zentitle2 MCP in Google ADK

You use `list_customers` and `get_customer_details`. The agent runs these tools to pull up current account data, which the Gemini model then processes against other enterprise resources in your Google Cloud setup.

Your agent calls `create_entitlement` to provision access. It can also check what's already active using `list_entitlements`. This ensures that your Gemini model doesn't hallucinate a required entitlement.

Yes. The agent can generate codes via `create_activation_code` and then list all records using `list_activation_codes`. This provides a full audit trail that integrates well with Vertex AI.

Yes. Since the MCP Server is built to connect with BigQuery and supports long-context reasoning, it's meant for agents performing complex tasks across your entire Google Cloud infrastructure.

It handles customer profiles and licensing details. Specifically, the `get_customer_details` tool exposes the necessary account information for your agent to read and act upon within Google Cloud.

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