How to Use the Zillow MCP in OpenAI Agents SDK

Q: If I need detailed tax info on Zillow, how does the OpenAI Agents SDK help?

Use the getpropertybyid tool. It explicitly returns tax information alongside price history and features, giving your agent the full scope of data it needs.

Q: What kind of property details does Zillow provide when using OpenAI Agents SDK?

The searchproperty function provides core residential metrics like lot size, year built, and status. The system returns a structured JSON object detailing these fields.

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Connect Zillow MCP to OpenAI Agents SDK

Create your Vinkius account to connect Zillow to OpenAI Agents SDK 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 OpenAI Agents SDK

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Search US homes and rentals using the MCP Server

The `search_property` tool lets you find residential listings across the U.S. You just need an address, city, or zip code to start. It returns core data points like price, bedrooms, bathrooms, square footage, lot size, and year built. This search function gives your agents a quick snapshot of properties in any area. If you're building an agent system that needs to cross-reference large datasets, this MCP Server is a solid starting point.

Check full history on one property

When you use the `get_property_by_id` tool, your agents get more than just current info. You receive the full deal: address, tax records, price history, features, photos, and a detailed description. This is crucial for deeper analysis. Instead of guessing at market trends, your agent can pull verifiable data like past sale prices or specific property details from this MCP Server.

Find available rental listings

The `get_rental_property` tool lets you search for rentals specifically. It returns essential metrics like the rent price, number of bedrooms and bathrooms, square footage, and property type. This makes it easy to build specialized agents focused solely on the rental market. Your agent can quickly compare several listings using only the data provided by this MCP Server.

Setup guide

Set up Zillow MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Zillow tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Zillow tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Zillow tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Zillow Agent",
            instructions="You have access to Zillow tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Zillow MCP in OpenAI Agents SDK

You pass the desired address, city, or zip code to the agent. The `search_property` tool handles the request and returns structured data about available residential listings.

Yes. Since agents auto-discover MCP tools, you can configure a workflow where one specialized agent runs `search_property` for an area and passes that data to another agent for comparison.

Use the `get_property_by_id` tool. It explicitly returns tax information alongside price history and features, giving your agent the full scope of data it needs.

The `search_property` function provides core residential metrics like lot size, year built, and status. The system returns a structured JSON object detailing these fields.

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

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