What types of hotels use Mews?

Mews serves 5,000+ properties in 85+ countries — from boutique hotels and hostels to luxury resorts and hotel groups. It's a cloud-native PMS designed for modern hospitality.

Is the Mews API suitable for large hotel groups?

Yes, Mews provides a robust API that supports multi-property operations, making it ideal for hotel groups to manage central reservations, corporate billing, and group-wide reporting.

Can I check room housekeeping status in real-time?

Yes, you can query Mews to get the real-time status of any room, including whether it is clean, dirty, inspected, or out of order, which helps prioritize housekeeping efforts.

Mews MCP Server for Pydantic AI 12 tools — connect in under 2 minutes

Name: Mews
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 12 Tools SDK

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 Mews "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())

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* 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 Mews MCP Server

Connect your Mews hotel to any AI agent and transform your front desk into an intelligent, voice-ready concierge.

Pydantic AI validates every Mews 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

Reservations — Today's check-ins, upcoming arrivals, room assignments, and booking status
Guests — Search profiles, loyalty tiers, preferences, allergies, and past stays
Rooms — Real-time room status: vacant/occupied, housekeeping (clean/dirty/inspected)
Billing — Guest folios, charges, payments, and balance tracking
Rates & Services — Rate plans, bookable services, and POS outlet items
Property — Hotel configuration, departments, and operational settings

The Mews 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.

How to Connect Mews to Pydantic AI via MCP

Follow these steps to integrate the Mews MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

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

Explore tools

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

Why Use Pydantic AI with the Mews MCP Server

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

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

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

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

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

Mews + Pydantic AI Use Cases

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

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

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

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

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

Mews MCP Tools for Pydantic AI (12)

These 12 tools become available when you connect Mews to Pydantic AI via MCP:

get_guest

Get guest profile

get_property_info

Get hotel configuration

get_reservation

Get reservation details

get_reservations

Filter by date range. THE core tool — "Who is checking in today?" "How many rooms tonight?" Get hotel reservations

list_bills

Filter by guest for their complete financial history. List guest bills

list_outlet_items

With pricing and categories. List POS items

list_payments

With amounts, dates, and settlement status. List payments

list_rates

With pricing, restrictions, and availability rules. List room rates

list_room_blocks

With dates, room types, and release dates. List room blocks

list_rooms

List hotel rooms

list_services

List hotel services

search_guests

Returns profile, contact info, nationality, loyalty status, past stays, preferences, and billing history. Search hotel guests

Example Prompts for Mews in Pydantic AI

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

"Who is checking in today and are there any VIP guests?"

"Show me the housekeeping status for the 3rd floor."

"What is our average daily rate (ADR) for this weekend?"

Troubleshooting Mews MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Mews + Pydantic AI FAQ

Common questions about integrating Mews MCP Server with Pydantic AI.

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.

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.

Can I switch LLM providers without changing MCP code?

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