How to Use the Fidelizador MCP in Google ADK

Feed your BigQuery loyalty data directly into Gemini agents using Google ADK and the Fidelizador server.

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Connect Fidelizador MCP to Google ADK

Create your Vinkius account to connect Fidelizador 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 Fidelizador with Google ADK

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Enterprise loyalty routing with Google ADK

Connect your Gemini models directly to active Fidelizador marketing segments via Google ADK. By using `list_mailing_lists` and `create_mailing_list` within your Google ADK pipeline, your agent can analyze customer behavior in BigQuery and immediately organize users into targeted cohorts. The Google ADK framework handles execution layers, allowing enterprise agents to act on real-time Fidelizador database changes. This means your Gemini agent can automatically run `create_contact` to sync cloud databases with Fidelizador.

Run long-context analysis on campaign metrics

Gemini's massive context window in Google ADK is perfect for analyzing complex Fidelizador marketing histories. Use the Google ADK to pull extensive performance logs with `list_campaigns` and feed the raw output directly into your agent's reasoning loop. Your Gemini agent can parse thousands of lines of Fidelizador campaign data to find underperforming segments. It can then call `get_campaign` to inspect specific Fidelizador reward structures and draft copy within Google ADK.

Manage contacts securely via this MCP Server

Keep your Fidelizador customer database clean without writing manual Google ADK sync scripts. With tools like `update_contact` and `delete_contact` exposed to your Google ADK agent, you can automate routine Fidelizador maintenance. If a customer requests data removal, your Google ADK agent updates Fidelizador instantly. It queries the database using `list_contacts` to find the matching Fidelizador record and applies changes automatically.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Fidelizador. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about Fidelizador MCP in Google ADK

Install the package, define your connection parameters with your Vinkius token, and pass the toolset directly to your LlmAgent. Your Gemini models will immediately recognize the customer management tools.

Yes, the framework allows you to pass a specific list of tool names during initialization. You can expose only read tools like `list_campaigns` while blocking write operations.

Gemini's million-token window easily digests the complete payloads from `list_contacts` and campaign reports. The agent can analyze entire lists in a single turn without hitting token limits.

Absolutely. You can build an agent that queries purchase history from BigQuery and then calls `update_contact` to adjust loyalty points based on that spend.

The integration relies on Google Cloud's secure IAM controls alongside the Vinkius zero-trust sandbox. Your customer emails and campaign performance metrics are never exposed to public training sets and run in isolated execution environments.

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