How to Use the Zinrelo MCP in Google ADK

Q: Does Zinrelo help analyze membership data with the Google ADK?

The listmembertransactions tool provides raw transaction history that feeds perfectly into BigQuery. Your agents can pull this data and then perform advanced queries in your existing GCP infrastructure.

Run enterprise loyalty processes with the Google ADK using Zinrelo MCP Server.

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Connect Zinrelo MCP to Google ADK

Create your Vinkius account to connect Zinrelo 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 Zinrelo with Google ADK

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Execute Core Loyalty Functions via MCP Server

Your agents can perform critical tasks against your customer base. They'll manage point accrual, whether through purchases (`award_points_purchase`) or custom activities (`award_points_activity`). This keeps loyalty programs active and accurate. Agents also handle member lifecycle management using `enroll_member` and provide a full list of users via `list_loyalty_members`. These functions act as powerful, structured tools for your Gemini-powered agents.

Access Deep Member History

You can get detailed reports on any user. The agent retrieves specific member profiles using `get_member_details` and compiles a complete history of all points changes with `list_member_transactions`. This data easily feeds into BigQuery for deeper analysis. If you need to understand the program rules, `get_loyalty_settings` gives your agents the exact parameters they need.

Control Rewards and Points

The MCP Server lets your agents fully control point balances. They can deduct points manually with `deduct_points`, or allow users to redeem rewards using `redeem_reward`. This centralized control means all actions are traceable within Vertex AI. Running these tools through the Google ADK ensures that complex, multi-step business processes are handled reliably in an enterprise environment.

Setup guide

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

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Common questions about Zinrelo MCP in Google ADK

The MCP Server integrates as a structured toolset within your LlmAgent. Your agents treat it like any other data source, calling specific functions to manage loyalty program actions.

Yes. Because Gemini models support long context (1M+ tokens), your agents can hold and process all necessary information from multiple tool calls, ensuring a cohesive workflow.

The `list_member_transactions` tool provides raw transaction history that feeds perfectly into BigQuery. Your agents can pull this data and then perform advanced queries in your existing GCP infrastructure.

It is built for enterprise use cases. The integration supports Stdio and HTTP transports, making it resilient enough for large-scale daily operations on Google Cloud.

This MCP Server handles customer account data, specifically point balances, member IDs, and detailed transaction records. You'll need to ensure BigQuery has appropriate schema mapping for this data.

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