3,400+ MCP servers ready to use
Vinkius

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

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Urbanise through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this App Connector for Pydantic AI

The Urbanise app connector for Pydantic AI 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
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Urbanise "
            "(12 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Urbanise?"
    )
    print(result.data)

asyncio.run(main())
Urbanise
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
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.

Pydantic AI validates every Urbanise tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

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 Pydantic AI 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 Pydantic AI

When Pydantic AI 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 Pydantic AI via MCP

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

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 12 tools from Urbanise with type-safe schemas

Why Use Pydantic AI with the Urbanise MCP Server

Pydantic AI provides unique advantages when paired with Urbanise through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Urbanise integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Urbanise connection logic from agent behavior for testable, maintainable code

Urbanise + Pydantic AI Use Cases

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

01

Type-safe data pipelines: query Urbanise with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Urbanise tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Urbanise and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Urbanise responses and write comprehensive agent tests

Example Prompts for Urbanise in Pydantic AI

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

01

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

02

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

03

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

Troubleshooting Urbanise MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Urbanise + Pydantic AI FAQ

Common questions about integrating Urbanise MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Urbanise MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.