How to Use the Mews MCP in Pydantic AI

Q: How does the MCP Server keep my hotel's financial data secure?

All financial records fetched via listbills or listpayments are processed through secure, ephemeral V8 isolates on Vinkius. No transactional data is cached or stored, maintaining strict isolation for your property's billing operations.

Run type-safe Mews operations using Pydantic AI to validate guest, reservation, and billing data at runtime.

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Connect Mews MCP to Pydantic AI

Create your Vinkius account to connect Mews 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 Mews with Pydantic AI

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Type-Safe Guest and Profile Queries

`get_guest` retrieves a specific guest profile, validating the returned contact details and loyalty status against strict Python schemas. If Mews returns unexpected data fields, Pydantic AI raises a validation error immediately. This prevents your agent from processing corrupted profiles or making decisions based on malformed API payloads. By using this MCP Server, your code guarantees that each guest object matches your expected data structure before any business logic runs.

Pydantic AI Reservation and Rate Validation

`get_reservations` pulls reservation records within a date range, forcing each record to conform to your defined models. Your agent can safely run `list_rates` to check pricing rules, knowing the data is structurally sound. This strict runtime validation is critical when managing room inventory. It ensures that booking dates, room types, and rate restrictions are 100% accurate before your agent confirms a booking change.

Validated Billing and Financial Auditing

`list_bills` retrieves complete financial histories for guests, mapping outstanding balances directly to type-safe Python objects. The agent uses `list_payments` to check settlement statuses without risking silent data parsing failures. Because Pydantic AI is model-agnostic, you can use these tools with any LLM provider while maintaining strict data integrity. The agent can audit billing records and flag discrepancies without hallucinating financial fields.

Setup guide

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

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

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

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Common questions about Mews MCP in Pydantic AI

Install the slim package with MCP support and initialize MCPToolset with your Vinkius HTTP endpoint. Pass the toolset to your Agent's toolsets parameter to expose all 12 PMS tools.

The framework fails loudly at runtime with a validation error. This prevents your agent from executing decisions based on corrupted reservation or billing data.

Yes, the MCPToolset in Pydantic AI supports both streamable HTTP and SSE transports, allowing you to connect to your externally managed Vinkius server.

Yes, Pydantic AI is completely model-agnostic. You can run your Mews workflows using local models or any major cloud LLM provider while keeping the same type-safe tools.

All financial records fetched via `list_bills` or `list_payments` are processed through secure, ephemeral V8 isolates on Vinkius. No transactional data is cached or stored, maintaining strict isolation for your property's billing operations.

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