How to Use the Urbanise MCP in Pydantic AI

Q: How does Urbanise help with maintenance jobs using Pydantic AI?

You can schedule a job with createmaintenancejob. Because of the type validation, you're guaranteed that the required title and description fields are correctly received by the API.

Q: Can I list all property plans with Urbanise and Pydantic AI?

Yes. The listpropertyplans tool fetches a complete set of property plans, ensuring that every field you read matches the expected schema.

Q: What data does Urbanise touch regarding supplier information when using Pydantic AI?

The server provides vendor details through listmanagedsuppliers. These records are type-validated, so your agent always processes clean supplier lists.

Q: Is the financial data reliable with Urbanise and Pydantic AI?

Extremely. When you call listfinancialdata, the response is validated against a schema. This means bad or unexpected ledger/billing information will trigger an error instead of corrupting your process.

Manage community properties with Pydantic AI. Get type-safe results for everything from occupancy lists to maintenance tasks.

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Connect Urbanise MCP to Pydantic AI

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

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Setup Urbanise with Pydantic AI

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Handling Occupancy Data

You'll get a list of residents and owners using `list_property_occupants`. This data is strictly typed, so you never get unexpected fields. Likewise, knowing the core structure via `list_property_plans` comes back clean. Your agent trusts this MCP Server because it validates every record against Pydantic models.

Managing Facility Assets

When you run `list_facility_assets`, the data structure is guaranteed. You know exactly what equipment details to expect, preventing runtime errors from unexpected API responses. This level of type safety makes building reliable production agents possible.

Financial Oversight

The financial tools are rock solid. Getting ledger data with `list_accounting_ledgers` or retrieving billing records via `list_financial_data` both return predictable, validated types. If the API messes up and returns garbage, your agent fails loudly—you know immediately.

Setup guide

Set up Urbanise MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "urbanise-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Urbanise tools.",
)

result = await agent.run("List recent Urbanise transactions")
print(result.output)

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Common questions about Urbanise MCP in Pydantic AI

You can schedule a job with `create_maintenance_job`. Because of the type validation, you're guaranteed that the required title and description fields are correctly received by the API.

Yes. The `list_property_plans` tool fetches a complete set of property plans, ensuring that every field you read matches the expected schema.

The server provides vendor details through `list_managed_suppliers`. These records are type-validated, so your agent always processes clean supplier lists.

Extremely. When you call `list_financial_data`, the response is validated against a schema. This means bad or unexpected ledger/billing information will trigger an error instead of corrupting your process.

This server manages authenticated client details, which you pull using `get_client_profile`. The result is always a validated object matching the required types.

Use it with your favorite AI tools

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

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