How to Use the StayFi MCP in Pydantic AI

Q: When I query guests using StayFi with Pydantic AI?

You can use searchguests or getguest. Because the response must match your defined model, you're protected from receiving unexpected fields or corrupted data formats.

Q: How does StayFi with Pydantic AI handle property lists?

Calling listproperties returns a validated list of properties. This ensures that every single property ID and associated metadata field is present and correctly typed when your agent receives it.

Ensure data integrity with Pydantic AI on the MCP Server.

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Connect StayFi MCP to Pydantic AI

Create your Vinkius account to connect StayFi to Pydantic AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup StayFi with Pydantic AI

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Verify Device Status and Connectivity

Need to know if hardware is working? Use `get_device_status`. This tool returns structured data on every device, letting you confirm operational status. If the API output doesn't match your expected model, Pydantic AI will fail loudly. This immediate failure notice prevents silent corruption in your agent system—a huge win for production deployments.

Check Overall StayFi Server Health

Before running any other tool, verify the core connection using `check_stayfi_status`. This gives a single boolean confirmation of the entire MCP Server's operational status. It’s crucial to run this first. If it fails, you know immediately that nothing else matters until the underlying connection is fixed.

List and Check WiFi Networks

Manage site connectivity using `list_networks` or getting specific details with `get_network`. These tools provide structured lists of all available WiFi networks and their current performance. Because the response is validated, you'll always get a predictable JSON structure to work with, regardless of what StayFi sends back.

Setup guide

Set up StayFi 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": {
        "stayfi-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by StayFi. 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.

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Common questions about StayFi MCP in Pydantic AI

You pass the MCP Toolset object directly to your Agent. The core benefit here is that every time data comes back—whether it's a list of properties or guest details—Pydantic validates its structure against your defined Python models.

This MCP Server handles property information, device hardware lists (`list_devices`), and network connectivity metrics. The most sensitive data type here is structured technical telemetry.

You can use `search_guests` or `get_guest`. Because the response must match your defined model, you're protected from receiving unexpected fields or corrupted data formats.

Calling `list_properties` returns a validated list of properties. This ensures that every single property ID and associated metadata field is present and correctly typed when your agent receives it.

The agent fails immediately with a validation error. There's no silent corruption; the framework forces you to address the malformed output before proceeding, guaranteeing correctness over speed.

Use it with your favorite AI tools

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

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