Bridge Data Output MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Bridge Data Output as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Bridge Data Output. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Bridge Data Output?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Bridge Data Output tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Bridge Data Output MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the Bridge Data Output MCP Server
LlamaIndex provides unique advantages when paired with Bridge Data Output through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Bridge Data Output tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Bridge Data Output tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Bridge Data Output, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Bridge Data Output tools were called, what data was returned, and how it influenced the final answer
Bridge Data Output + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Bridge Data Output MCP Server delivers measurable value.
Hybrid search: combine Bridge Data Output real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Bridge Data Output to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Bridge Data Output for fresh data
Analytical workflows: chain Bridge Data Output queries with LlamaIndex's data connectors to build multi-source analytical reports
Bridge Data Output MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Bridge Data Output to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Bridge Data Output to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBridge Data Output + LlamaIndex FAQ
Common questions about integrating Bridge Data Output MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Bridge Data Output with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Bridge Data Output to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.