How to Use the Urbanise MCP in OpenAI Agents SDK
Manage community properties with your OpenAI Agents SDK. Automate operations, from maintenance scheduling to financial reporting.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Urbanise MCP to OpenAI Agents SDK
Create your Vinkius account to connect Urbanise 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.
Scheduling Maintenance Jobs
You can use the `create_maintenance_job` tool to schedule new tasks quickly. Just provide a job title and description, and it gets logged right away. This lets your agents proactively manage facility upkeep without needing human intervention for basic scheduling.
Managing Property Data
Need to know who lives where? The `list_property_occupants` tool pulls a list of all residents and owners. You can also check the core data set using `list_property_plans`, which lists every plan associated with the community. This gives your AI client a full picture of the property's people and its physical structure.
Financial Reporting
The system handles all the money stuff. You can get ledger details using `list_accounting_ledgers` or pull specific billing information with `list_financial_data`. It keeps track of budgets too, via `list_property_budgets`. Your agent uses these tools to give financial overviews to property managers.
Set up Urbanise MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all Urbanise tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Urbanise tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Urbanise tools and returns structured results. Copy the full example on the right to get started.
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="Urbanise Agent",
instructions="You have access to Urbanise tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) 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.
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 OpenAI Agents SDK
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