How do I get Vagaro API access?

Go to your Vagaro dashboard → Settings → Developer Features → API Settings. You'll need Admin or Owner permissions and active payment processing to generate API credentials.

Does it support multi-location businesses?

Yes. Each location has its own Business ID. Configure the server with the specific Business ID for the location you want to manage, or set up multiple instances for multi-location oversight.

Vagaro MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Vagaro
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

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

    result = await agent.run(
        "What tools are available in Vagaro?"
    )
    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 Vagaro MCP Server

Connect your Vagaro business to any AI agent and manage your salon, spa, or fitness studio through natural conversation.

Pydantic AI validates every Vagaro tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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

Appointments — View booked appointments, check availability, and manage daily schedule
Clients — Search customers, view profiles, visit history, and preferences
Staff — List providers, check individual schedules, and manage availability
Services — Browse all services offered with pricing and duration
Classes — View group fitness classes, capacity, and enrollment
Products — Manage retail inventory: hair care, skincare, supplements
Business — Access business profile, hours, and online booking settings

The Vagaro MCP Server exposes 10 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 Vagaro to Pydantic AI via MCP

Follow these steps to integrate the Vagaro 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 10 tools from Vagaro with type-safe schemas

Why Use Pydantic AI with the Vagaro MCP Server

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

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

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

Vagaro + Pydantic AI Use Cases

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

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

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

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

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

Vagaro MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Vagaro to Pydantic AI via MCP:

get_appointment

Get appointment details

get_business_info

Get business profile

get_client

Get client profile

get_staff_schedule

Shows booked and available time slots. Get staff member schedule

list_appointments

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

list_classes

Includes schedule, instructor, capacity, and enrolled count. List fitness/wellness classes

list_products

Includes name, price, brand, and stock level. List retail products

list_services

Includes pricing, duration, and category. List all services offered

list_staff

Includes name, role, specialties, and availability. List all staff/providers

search_clients

Returns contact info, visit history, and preferences. Search clients/customers

Example Prompts for Vagaro in Pydantic AI

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

"Show me today's appointments."

"Find Elena Gomez's profile and check her last booked service."

"Book a 60-minute deep tissue massage for Mark Smith with John next Friday at 2 PM."

Troubleshooting Vagaro MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Vagaro + Pydantic AI FAQ

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