Can I create a new maintenance job for a property via AI?

Yes! Use the `create_maintenance_job` tool and provide a title and description. This will instantly register a new task in the Facility Management (FM) module.

How do I see all residents living in a specific property plan?

Run the `list_property_occupants` query. Your agent will retrieve the complete list of owners and residents across your managed property plans.

Is it possible to check the remaining budget for a building via AI?

Absolutely. Use the `list_property_budgets` query to retrieve the current budget definitions and allocations for your managed properties.

INSTANT PLUG AND PLAY

Urbanise MCP Server for CrewAIGive CrewAI instant access to 12 tools to Check Api Health, Create Maintenance Job, Get Client Profile, and more

Name: Urbanise
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Urbanise through Vinkius, pass the Edge URL in the `mcps` parameter and every Urbanise tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

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The Urbanise app connector for CrewAI is a standout in the Erp Operations category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Urbanise Specialist",
    goal="Help users interact with Urbanise effectively",
    backstory=(
        "You are an expert at leveraging Urbanise tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Urbanise "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

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

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Urbanise MCP Server

Connect your Urbanise property management account to any AI agent and simplify how you coordinate building operations, financial records, and community engagement through natural conversation.

When paired with CrewAI, Urbanise becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Urbanise tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Property Management — List all property plans and retrieve detailed metadata for your managed ecosystem.
Occupant & Strata Support — List residents and owners to manage communications and community directories.
Maintenance Control — Create, list, and track maintenance jobs and facility tasks directly from your agent.
Financial Visibility — Query ledger data, billing records, and property budgets to stay on top of your accounts.
Supply Chain — List managed suppliers and service providers associated with your property plans.
Asset Tracking — Monitor building equipment and infrastructure assets managed in the FM module.

The Urbanise MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Urbanise tools available for CrewAI

When CrewAI connects to Urbanise through Vinkius, your AI agent gets direct access to every tool listed below — spanning strata-management, facility-management, building-operations, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

check_api_health

Verify Urbanise API connectivity

create_maintenance_job

Requires job title and description. Schedule a new maintenance task

get_client_profile

Get authenticated client details

list_accounting_ledgers

List chart of accounts

list_configured_webhooks

List active event webhooks

list_facility_assets

List infrastructure equipment

list_financial_data

Retrieve ledger and billing info

list_maintenance_jobs

List facility maintenance tasks

list_managed_suppliers

List property suppliers

list_property_budgets

List budgets for plans

list_property_occupants

List residents and owners

list_property_plans

List all property plans

Connect Urbanise to CrewAI via MCP

Follow these steps to wire Urbanise into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Urbanise

Why Use CrewAI with the Urbanise MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Urbanise through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Urbanise + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Urbanise MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Urbanise for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Urbanise, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Urbanise tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Urbanise against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Urbanise in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Urbanise immediately.

"List all property plans managed in my Urbanise account."

"Show me all active maintenance jobs for 'Sunset Heights'."

"Create a maintenance job: 'Fix leaking pipe in Room 402'."

Troubleshooting Urbanise MCP Server with CrewAI

Common issues when connecting Urbanise to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Urbanise + CrewAI FAQ

Common questions about integrating Urbanise MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.