Zenoti MCP Server for LlamaIndex 14 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Zenoti as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
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 Zenoti. "
"You have 14 tools available."
),
)
response = await agent.run(
"What tools are available in Zenoti?"
)
print(response)
asyncio.run(main())
* 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 Zenoti MCP Server
Connect your Zenoti organization to any AI agent and manage your spa, salon, or medspa enterprise through natural conversation.
LlamaIndex agents combine Zenoti tool responses with indexed documents for comprehensive, grounded answers. Connect 14 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
- 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 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 Zenoti to LlamaIndex via MCP
Follow these steps to integrate the Zenoti 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 14 tools from Zenoti
Why Use LlamaIndex with the Zenoti MCP Server
LlamaIndex provides unique advantages when paired with Zenoti through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Zenoti tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Zenoti tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Zenoti, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Zenoti tools were called, what data was returned, and how it influenced the final answer
Zenoti + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Zenoti MCP Server delivers measurable value.
Hybrid search: combine Zenoti real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Zenoti 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 Zenoti for fresh data
Analytical workflows: chain Zenoti queries with LlamaIndex's data connectors to build multi-source analytical reports
Zenoti MCP Tools for LlamaIndex (14)
These 14 tools become available when you connect Zenoti to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Zenoti to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpZenoti + LlamaIndex FAQ
Common questions about integrating Zenoti MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Zenoti with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Zenoti to LlamaIndex
Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.