How to Use the Zillow MCP in Google ADK

Q: How can I integrate Zillow search into my Google ADK flow?

You use the searchproperty tool within your LlmAgent. The output is a structured data payload that BigQuery or Vertex AI models can consume immediately for reasoning.

Q: What if I need detailed history on Zillow properties using Google ADK?

The getpropertybyid tool provides the full historical record, including price changes and tax data. This is designed to support long-context reasoning within your enterprise agent.

Q: Can I use Zillow rental listings with Google ADK?

Absolutely. The getrentalproperty tool handles the necessary search, returning key metrics like rent price and square footage for analysis in your cloud environment.

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Connect Zillow MCP to Google ADK

Create your Vinkius account to connect Zillow 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 Zillow with Google ADK

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Search property listings for BigQuery analysis

Run the `search_property` tool to gather massive datasets of residential properties. The results include address, price, bedrooms, bathrooms, square footage, and lot size. You can pipe this structured data directly into your Google Cloud infrastructure via the ADK setup, allowing for complex analysis using BigQuery.

Get deep property context with Zillow MCP Server

The `get_property_by_id` tool delivers full property details—everything from tax info and price history to features and descriptions. This depth of data is perfect for enterprise use cases. By feeding this information into your Gemini models, you allow your agents to perform reasoning that goes way beyond simple lookups.

Identify rental markets using Google ADK

Use `get_rental_property` when you need to analyze the rental market. It returns listings with rent price, bed/bath count, square footage, and property type. This lets your agents build multi-stage pipelines: first searching for an area, then validating specific rentals against that search criteria.

Setup guide

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

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Common questions about Zillow MCP in Google ADK

You use the `search_property` tool within your LlmAgent. The output is a structured data payload that BigQuery or Vertex AI models can consume immediately for reasoning.

The `get_property_by_id` tool provides the full historical record, including price changes and tax data. This is designed to support long-context reasoning within your enterprise agent.

Absolutely. The `get_rental_property` tool handles the necessary search, returning key metrics like rent price and square footage for analysis in your cloud environment.

The server touches detailed property information including address, tax info, description, photos, and historical pricing data.

This server touches property details, including address, price history, tax information, descriptions, and photos.

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