Can I filter listings by a specific price range?

Yes! Use the `search_properties_by_price` tool and provide the minimum price. You can also use the `list_properties` tool with a custom OData `$filter` for more complex criteria.

How do I see which MLS datasets I have access to?

Simply ask the agent to `list_data_systems`. It will return a list of all data sources currently enabled for your server token.

Does the integration provide access to property photos?

Yes. Use the `list_media` tool with the Dataset ID. It will retrieve the media associated with the properties, providing URLs for images and virtual tours.

Bridge Data Output MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Bridge Data Output
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Bridge Data Output through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Bridge Data Output "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Bridge Data Output?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Bridge Data Output MCP Server

Connect your Bridge Interactive (Zillow Group) account to any AI agent and orchestrate your real estate research, listing analysis, and market data workflows through natural conversation.

Pydantic AI validates every Bridge Data Output tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Listing Oversight — Browse thousands of real estate listings (properties) from various MLS datasets with advanced OData filtering.
Property Deep Dives — Retrieve detailed metadata for specific properties, including physical characteristics and historical values.
Directory Access — List real estate members (agents) and offices associated with specific datasets.
Media Management — Access links to high-resolution photos, virtual tours, and media associated with property listings.
Market Analysis — Search for properties by city, price range, or recent modifications to track market trends.
Dataset Discovery — List all available data systems (MLSs) your application has access to.

The Bridge Data Output MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Bridge Data Output to Pydantic AI via MCP

Follow these steps to integrate the Bridge Data Output MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Bridge Data Output with type-safe schemas

Why Use Pydantic AI with the Bridge Data Output MCP Server

Pydantic AI provides unique advantages when paired with Bridge Data Output through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Bridge Data Output integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Bridge Data Output connection logic from agent behavior for testable, maintainable code

Bridge Data Output + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Bridge Data Output MCP Server delivers measurable value.

Type-safe data pipelines: query Bridge Data Output with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Bridge Data Output tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Bridge Data Output and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Bridge Data Output responses and write comprehensive agent tests

Bridge Data Output MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Bridge Data Output to Pydantic AI via MCP:

get_dataset_metadata

Get schema metadata for a specific dataset

get_property

Get details of a specific property

list_data_systems

List all available real estate data systems (MLSs)

list_media

List media (photos/videos) from a dataset

list_members

List real estate agents (members) from a dataset

list_offices

List real estate offices from a dataset

list_properties

List properties from a specific dataset

list_recent_listings

List the most recently modified properties

search_properties_by_city

Search for properties in a specific city

search_properties_by_price

Search for properties above a specific price

Example Prompts for Bridge Data Output in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Bridge Data Output immediately.

"List all real estate data systems I can access."

"Search for properties in Miami with a price over $1,000,000."

"Get details for property listing key 12345-6789."

Troubleshooting Bridge Data Output MCP Server with Pydantic AI

Common issues when connecting Bridge Data Output to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Bridge Data Output + Pydantic AI FAQ

Common questions about integrating Bridge Data Output MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Bridge Data Output MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.