How to Use the Urbanise MCP in LlamaIndex

Q: Can LlamaIndex help with Urbanise maintenance history?

Yes. By indexing results from listmaintenancejobs and listfacilityassets, you can query past work orders to understand why a specific piece of equipment failed, drawing details directly from the recorded job descriptions.

Q: Does LlamaIndex support querying Urbanise webhook configurations?

Yes. By indexing the output of listconfiguredwebhooks, you can ask questions like, 'Which webhooks are currently set up to trigger on owner profile changes?' This helps audit your system's event triggers.

Q: What data privacy concerns should I know about Urbanise and LlamaIndex?

This server touches resident names and addresses via listpropertyoccupants. Make sure you filter the index creation process to only include necessary data fields to protect personal information.

Building RAG Applications for Urbanise with LlamaIndex knowledge indexing.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Urbanise MCP to LlamaIndex

Create your Vinkius account to connect Urbanise to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Urbanise with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Query Historical Financial Records

LlamaIndex takes the output of `list_financial_data` and indexes it. Instead of just seeing a list, you can query past sessions to ask, 'What were the billing details for Unit 4B last quarter?' The system answers using actual ledger data. This means your knowledge base isn't theoretical; it’s built directly from Urbanise's live API calls.

Search Property Configuration and Assets

Use `list_property_plans` or `list_facility_assets` to populate an index. Later, you can query the index semantically: 'Show me all assets related to Phase Two plans.' LlamaIndex finds that connection in a way simple searching misses. It’s about building a searchable knowledge layer on top of structured data.

Retrieve Occupant and Management Details

The `list_property_occupants` tool populates an index of residents and owners. You can then ask complex questions like, 'Which property plans are associated with the primary owner listed in this profile?' LlamaIndex combines data from multiple sources—the occupant list and the plan list—to give a unified answer.

Setup guide

Set up Urbanise MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Urbanise MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Urbanise tools.",
)
response = await agent.run("List recent Urbanise data")

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 Urbanise. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Urbanise now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Urbanise MCP in LlamaIndex

It turns structured API output into searchable knowledge. Instead of just reading a large ledger from `list_accounting_ledgers`, you can ask targeted questions about specific accounts, grounding the answer in real data.

Yes. By indexing results from `list_maintenance_jobs` and `list_facility_assets`, you can query past work orders to understand why a specific piece of equipment failed, drawing details directly from the recorded job descriptions.

The main win is moving beyond simple list retrieval. You create applications where live data—like budgets or occupancy lists—become part of a unified, queryable knowledge index for your agents.

Yes. By indexing the output of `list_configured_webhooks`, you can ask questions like, 'Which webhooks are currently set up to trigger on owner profile changes?' This helps audit your system's event triggers.

This server touches resident names and addresses via `list_property_occupants`. Make sure you filter the index creation process to only include necessary data fields to protect personal information.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript