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 LlamaIndex 10 tools — connect in under 2 minutes

Name: Vagaro
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Vagaro as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Vagaro. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Vagaro?"
    )
    print(response)

asyncio.run(main())

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About Vagaro MCP Server

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

LlamaIndex agents combine Vagaro tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the Vagaro MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

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

Why Use LlamaIndex with the Vagaro MCP Server

LlamaIndex provides unique advantages when paired with Vagaro through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Vagaro tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Vagaro tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Vagaro, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Vagaro tools were called, what data was returned, and how it influenced the final answer

Vagaro + LlamaIndex Use Cases

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

Hybrid search: combine Vagaro real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Vagaro to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Vagaro for fresh data

Analytical workflows: chain Vagaro queries with LlamaIndex's data connectors to build multi-source analytical reports

Vagaro MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Vagaro to LlamaIndex 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 LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Vagaro + LlamaIndex FAQ

Common questions about integrating Vagaro MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Vagaro tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.