Bring Strata Management
to LlamaIndex
Learn how to connect Urbanise to LlamaIndex and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the 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.
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.
How it works
1. Subscribe to this server
2. Enter your Urbanise Region, Client ID, and Access Token
3. Start managing your properties and facility maintenance from Claude, Cursor, or any MCP client
Who is this for?
- Property Managers — quickly retrieve occupant lists and verify property budgets via simple AI commands.
- Facility Managers — schedule maintenance jobs and track asset health directly from the workspace.
- Strata Management Companies — coordinate supplier lists and monitor financial ledgers for entire property portfolios.
Built-in capabilities (12)
Verify Urbanise API connectivity
Requires job title and description. Schedule a new maintenance task
Get authenticated client details
List chart of accounts
List active event webhooks
List infrastructure equipment
Retrieve ledger and billing info
List facility maintenance tasks
List property suppliers
List budgets for plans
List residents and owners
List all property plans
Why LlamaIndex?
LlamaIndex agents combine Urbanise tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine Urbanise tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Urbanise tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Urbanise, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Urbanise tools were called, what data was returned, and how it influenced the final answer
Urbanise in LlamaIndex
Urbanise and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Urbanise to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Urbanise in LlamaIndex
The Urbanise 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. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Urbanise for LlamaIndex
Every tool call from LlamaIndex to the Urbanise MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
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.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query Urbanise tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp