How to Use the Leal MCP in Google ADK

Q: How is our customer transactional data secured in this cloud setup?

All raw transaction logs and member profiles fetched via listtransactions are processed in memory within your private Google Cloud VPC. Vinkius handles the underlying authentication tokens through an ephemeral sandbox, ensuring your API keys are never exposed to the public internet.

Connect Gemini to Leal data using the Google ADK to analyze retail transaction trends directly from your cloud databases.

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Connect Leal MCP to Google ADK

Create your Vinkius account to connect Leal 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 Leal with Google ADK

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Map retail locations to BigQuery datasets

The `list_stores` tool retrieves complete geographical and operational details for every retail outlet in your loyalty network. By feeding this raw store data directly into your Google ADK agent, you can cross-reference physical store locations with your existing cloud datasets. Your agent can query `get_store` to analyze performance metrics for specific branches. This allows Gemini to pinpoint which physical locations are driving the highest loyalty sign-ups without requiring manual data exports.

Analyze transactions with this Google ADK MCP Server

The `list_transactions` tool pulls historical sales and points data directly into Gemini's massive context window. Because the Google ADK handles long-context reasoning, your agent can process thousands of loyalty records at once to find hidden purchasing patterns. You can combine this transaction feed with customer segment data retrieved via `list_segments`. The agent then identifies which demographics are driving the highest sales volume, giving you clear insights to optimize your marketing spend.

Track campaign performance across your network

The `list_campaigns` tool outputs active promotions and marketing runs directly to your agent. This integration allows your Google Cloud enterprise agent to evaluate which campaigns are yielding the highest customer return rates. Since the MCP integration connects directly with Vertex AI, you can generate and test variations of these offers based on historical response rates. Your agent uses this campaign list to draft localized promotional offers for underperforming store branches.

Setup guide

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

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Common questions about Leal MCP in Google ADK

You initialize the toolset class with the HTTP transport URL provided by Vinkius. Once registered, your Gemini agent can call any of the 12 loyalty tools during a conversational session.

Yes, you can pass a list of specific tool names to the toolset constructor to restrict access. For instance, you can expose only `list_rewards` while hiding sensitive transaction tools.

The framework uses streamable HTTP transports to keep connection times low during live queries. If you experience network issues, your agent can call `check_leal_status` to verify the connection before attempting complex data retrievals.

Yes, this MCP Server supports both stdio and HTTP transports depending on how you deploy your agent. You can switch between them by changing the initialization parameters in your Python configuration.

All raw transaction logs and member profiles fetched via `list_transactions` are processed in memory within your private Google Cloud VPC. Vinkius handles the underlying authentication tokens through an ephemeral sandbox, ensuring your API keys are never exposed to the public internet.

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