How to Use the Zillow MCP in CrewAI

Q: How do I run a Zillow property deep dive with CrewAI?

You assign an agent to use getpropertybyid. The crew handles the entire process: research, analysis (tax info, price history), and final reporting autonomously.

Q: Can CrewAI manage Zillow rental listings?

Yes. You assign an agent to use getrentalproperty. The crew will automatically pass the retrieved listing details—like rent price and bathrooms—to a moderator for review.

Q: What is the best way to query Zillow with CrewAI?

Use searchproperty through the framework. This allows one agent to research addresses, another to analyze property types, and a third to compile the final list of results.

Run autonomous real estate operations with the CrewAI multi-agent framework.

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Create your Vinkius account to connect Zillow to CrewAI 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 CrewAI

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Autonomous Property Deep Dive

You set up a specialized research agent that uses `get_property_by_id`. This agent pulls all available details, including price history and photos. A second analysis agent can then take this raw data to generate reports. The crew operates autonomously, acting on the full property context without needing human intervention at each step.

Coordinated Rental Scouting

A specialized searcher agent uses `get_rental_property` to gather active listings. A moderator agent then compiles and filters this data based on your criteria. The process is hierarchical: the listing details are gathered, passed to the moderator, which validates them before output.

Structured Residential Area Mapping

The crew assigns a research role to gather data via `search_property`. This agent gets addresses and basic metrics like year built. The final action agent then takes this structured list and formats it into an output document. This multi-agent setup ensures that the raw search results are always processed through multiple specialized lenses.

Setup guide

Set up Zillow MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Zillow tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Zillow Analyst",
    goal="Access and analyze Zillow data via MCP.",
    backstory="Expert analyst with direct Zillow access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Zillow transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Zillow Analyst",
        goal="Access and analyze Zillow data via MCP.",
        backstory="Expert analyst with direct Zillow access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Zillow transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 Zillow. 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.

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Common questions about Zillow MCP in CrewAI

You assign an agent to use `get_property_by_id`. The crew handles the entire process: research, analysis (tax info, price history), and final reporting autonomously.

Yes. You assign an agent to use `get_rental_property`. The crew will automatically pass the retrieved listing details—like rent price and bathrooms—to a moderator for review.

Use `search_property` through the framework. This allows one agent to research addresses, another to analyze property types, and a third to compile the final list of results.

The crew structure is designed for robust operations. The monitor agent watches sessions, ensuring that if one step fails (like a search), the moderator can escalate or adjust the workflow.

The MCP Server touches property details including addresses, pricing, lot size, tax info, and listing status. The agents process these complex datasets collaboratively.

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