How to Use the Vagaro MCP in LlamaIndex

Q: How does LlamaIndex enhance Vagaro's booking process?

LlamaIndex takes the output from getappointment and indexes it. This lets your system answer complex questions about past bookings, like 'Which services did Client Y book three months ago?'

Q: Can I combine Vagaro data with other documents using LlamaIndex?

Absolutely. You can mix API results (like listproducts stock levels) and internal PDFs into one unified, queryable index for advanced RAG applications.

Q: If I need business info, how does Vagaro work with LlamaIndex?

You call getbusinessinfo, which returns the profile details. Indexing this data means you can query specific business rules or policies grounded in the live API documentation.

Build RAG systems for salon data using LlamaIndex and the Vagaro MCP Server.

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Connect Vagaro MCP to LlamaIndex

Create your Vinkius account to connect Vagaro to LlamaIndex 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 Vagaro with LlamaIndex

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Query Client History with MCP Server

The process starts by calling `search_clients` to pull contact info, visit history, and preferences. You index this entire result into your vector store. Now, you can ask questions like 'What was client X's last service?' and get an answer grounded in the actual API data.

Index Service Offerings

Want to search through services? Run `list_services` first. You index the pricing, duration, and category details into your knowledge base. This lets you build a semantic search that answers questions like 'What's cheaper than a massage?' rather than just listing results.

Search Staff Availability for Knowledge

Use `get_staff_schedule` to get booked and available time slots. This output becomes part of your searchable index, allowing you to query past scheduling constraints or check availability against historical data without running a live API call.

Setup guide

Set up Vagaro MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Vagaro MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Vagaro tools.",
)
response = await agent.run("List recent Vagaro data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Vagaro. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Vagaro MCP in LlamaIndex

LlamaIndex takes the output from `get_appointment` and indexes it. This lets your system answer complex questions about past bookings, like 'Which services did Client Y book three months ago?'

Absolutely. You can mix API results (like `list_products` stock levels) and internal PDFs into one unified, queryable index for advanced RAG applications.

You call `get_business_info`, which returns the profile details. Indexing this data means you can query specific business rules or policies grounded in the live API documentation.

Yes. You combine structured data from multiple tools, such as `list_staff` and `list_services`, into a single index for comprehensive querying power.

The server touches Client Profile and Appointment Data. When indexing, remember that visit history must be treated as sensitive PII.

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