How to Use the iZooto MCP in Google ADK

Q: How do I initialize the iZooto MCP Server inside Google ADK?

Instantiate McpToolset using StreamableHttpServerParameters pointing to your server. Then, pass that toolset instance directly into your LlmAgent tools list.

Q: How does Google ADK handle long-context reasoning with this iZooto MCP Server?

Gemini models can read previous notification history from listnotifications alongside massive customer tables to draft highly personalized push messages. This allows the agent to maintain high contextual relevance.

Drive browser traffic using Google ADK to trigger targeted iZooto push notifications based on enterprise data.

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Connect iZooto MCP to Google ADK

Create your Vinkius account to connect iZooto 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 iZooto with Google ADK

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Target segments using Google ADK and BigQuery

Gemini agents running on Google ADK can process millions of user data points from BigQuery to determine who needs to see a notification. The agent calls `create_segment` to build precise iZooto target lists based on SQL query results. This MCP Server integration allows your enterprise agent to run deep reasoning over long contexts before deciding which audience to target. You avoid guesswork by letting Google ADK match database trends with actual iZooto push segments.

Deliver contextual push campaigns automatically

Your Google ADK agent checks system readiness using `check_izooto_status` before initiating any high-volume broadcast. Once confirmed, it uses `send_segment_push` to send hyper-personalized notifications to specific user groups. Because the agent runs within the Google Cloud ecosystem, you can trigger these actions based on real-time Pub/Sub events. Tracking sent campaigns is handled by querying `list_notifications` to prevent duplicate messaging.

Process performance metrics in Vertex AI

Analyzing iZooto campaign performance is direct when your Google ADK agent uses `get_stats` to pull click-through metrics. The agent feeds these numbers back into Vertex AI to refine future message generation. It can also check `get_subscriber_count` to map audience growth trends over time. This MCP toolset setup ensures your marketing metrics are immediately available to your Google Cloud analytical pipelines.

Setup guide

Set up iZooto 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 iZooto 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="iZooto_agent",
    model="gemini-2.0-flash",
    instruction="You have access to iZooto tools via MCP.",
    tools=mcp_tools,
)

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Common questions about iZooto MCP in Google ADK

Instantiate `McpToolset` using `StreamableHttpServerParameters` pointing to your server. Then, pass that toolset instance directly into your `LlmAgent` tools list.

Yes, you can use the optional tool name filter in the toolset configuration. This lets you restrict access to sensitive tools like `send_push` while keeping read-only tools open.

Gemini models can read previous notification history from `list_notifications` alongside massive customer tables to draft highly personalized push messages. This allows the agent to maintain high contextual relevance.

No, Vinkius handles the underlying API authentication. Your agent only needs the single endpoint token to securely interact with all available tools.

All API traffic, including click-through rates and delivery statistics, is encrypted in transit and processed within ephemeral runtimes. No persistent storage of your notification content or subscriber metrics occurs on the platform.

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