Which brands use Zenoti?

Zenoti powers 30,000+ locations worldwide including Massage Envy, Hand & Stone, European Wax Center, Massage Heights, Woodhouse Spas, and thousands of independent luxury spas and salons.

Zenoti MCP Server for Pydantic AI 14 tools — connect in under 2 minutes

Name: Zenoti
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 14 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Zenoti 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 Zenoti "
            "(14 tools)."
        ),
    )

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

asyncio.run(main())

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About Zenoti MCP Server

Connect your Zenoti organization to any AI agent and manage your spa, salon, or medspa enterprise through natural conversation.

Pydantic AI validates every Zenoti tool response against typed schemas, catching data inconsistencies at build time. Connect 14 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

Guests — Search guests, view profiles, preferences, allergies, and loyalty points
Appointments — Browse bookings with therapist, room, service, and payment status
Services — List all spa/salon services with pricing, duration, and categories
Therapists — View providers with specialties, ratings, and availability
Invoices — Track revenue, sales, tips, and payment breakdowns
Memberships — Manage membership tiers: basic, premium, VIP, couples
Packages — Browse bundled services: couples massage, day spa, bridal
Gift Cards — Track gift card balances, sales, and redemptions
Centers — Manage multi-location operations across your enterprise

The Zenoti MCP Server exposes 14 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 Zenoti to Pydantic AI via MCP

Follow these steps to integrate the Zenoti 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 14 tools from Zenoti with type-safe schemas

Why Use Pydantic AI with the Zenoti MCP Server

Pydantic AI provides unique advantages when paired with Zenoti 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 Zenoti integration code

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

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

Zenoti + Pydantic AI Use Cases

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

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

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

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

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

Zenoti MCP Tools for Pydantic AI (14)

These 14 tools become available when you connect Zenoti to Pydantic AI via MCP:

get_appointment

Get appointment details

get_center

Get center details

get_guest

Get guest profile

get_guest_loyalty

Get guest loyalty points

list_appointments

Filter by date to see a specific day. List spa/salon appointments

list_centers

Includes name, address, timezone, and operating hours. Essential for multi-location spa chains like Massage Envy. List spa/salon locations

list_employees

Includes role, schedule, payroll info, and commission structure. List all employees

list_gift_cards

Filter by guest to see a specific person's cards. List gift cards

list_invoices

Filter by date range for revenue analysis. List sales and invoices

list_memberships

Shows pricing, included services, visit limits, and perks. List membership plans

list_packages

Shows included services and pricing. List service packages

list_services

Includes pricing, duration, category, and required room type. List spa/salon services

list_therapists

List therapists and providers

search_guests

Returns profile, visit history, loyalty points, preferred therapist, and product preferences. Search spa/salon guests

Example Prompts for Zenoti in Pydantic AI

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

"Show today's appointments at the downtown center."

"Find the profile for guest Maria Gonzalez and check her loyalty points."

"What is the total revenue collected across all centers today?"

Troubleshooting Zenoti MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Zenoti + Pydantic AI FAQ

Common questions about integrating Zenoti 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 Zenoti MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.