How to Use the StayFi MCP in Google ADK

Q: How do I use StayFi with Google ADK?

You initialize the toolset using McpToolset and pass it to your LlmAgent. Since you're building enterprise agents, this method integrates naturally with BigQuery and Vertex AI.

Q: What specific data does StayFi touch in Google ADK?

This MCP Server deals with guest records (exportguests), property metrics, and overall network status. The primary data type you're managing is structured business metadata.

Q: If I need to query specific guests using StayFi with Google ADK?

You can use listguests or searchguests. These tools allow your agent to pull granular details on individuals, which you then pipe into BigQuery for deeper analysis.

Q: Does StayFi with Google ADK provide connectivity checks?

Yes. The getnetwork tool provides real-time network data. Your agent can use this information to determine if a property is operational before running complex queries against it.

Process massive StayFi data with Google ADK.

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Connect StayFi MCP to Google ADK

Create your Vinkius account to connect StayFi to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup StayFi with Google ADK

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Export Full Guest Records

Need to feed raw guest lists into BigQuery? Use the `export_guests` tool. This function pulls all necessary data fields, preparing a clean dataset for large-scale analysis. The output is perfect for batch processing within Google Cloud. Your agent can then push this structured data directly into your enterprise data warehouse.

Get Property Statistics via MCP Server

Run high-level reports on multiple properties using `get_property_stats`. This tool aggregates performance metrics, giving you an immediate picture of operational health across a chain. It's designed for the BigQuery workflow. Your agent can process these stats and write findings directly to your connected data tables.

List All Managed Properties

Start by getting a full list of all available locations using `list_properties`. This function provides every property ID, which is necessary before running any other location-specific check. Because your agent uses Google ADK, it can handle massive lists and pass them through the cloud infrastructure efficiently.

Setup guide

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

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Common questions about StayFi MCP in Google ADK

You initialize the toolset using `McpToolset` and pass it to your LlmAgent. Since you're building enterprise agents, this method integrates naturally with BigQuery and Vertex AI.

Absolutely. The system supports long-context reasoning using Gemini models that can process over 1 million tokens. This is ideal when querying massive, exported datasets.

This MCP Server deals with guest records (`export_guests`), property metrics, and overall network status. The primary data type you're managing is structured business metadata.

You can use `list_guests` or `search_guests`. These tools allow your agent to pull granular details on individuals, which you then pipe into BigQuery for deeper analysis.

Yes. The `get_network` tool provides real-time network data. Your agent can use this information to determine if a property is operational before running complex queries against it.

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