How to Use the Acuity Scheduling MCP in LlamaIndex

Q: How can LlamaIndex help me understand my Acuity Scheduling business better?

By indexing the output of tools like listappointments and listclasses over time. This creates a searchable history, letting your LlamaIndex agent answer questions about past booking trends and service popularity.

Q: Can I filter appointments by date?

Yes, the listappointments tool includes a date range filter. You can build your LlamaIndex agent to fetch and index appointments month by month, for example.

Q: Does this work with multiple providers in Acuity Scheduling and LlamaIndex?

It does. Call listcalendars to get the IDs for all your providers. You can then use those IDs to filter other queries or build separate knowledge bases for each provider's schedule in your LlamaIndex app.

Q: Can I check enrollment for a group class in Acuity Scheduling with LlamaIndex?

Yes. The listclasses tool returns all scheduled classes, including their capacity and how many people have enrolled. Your agent can use this to see which classes are popular or nearly full.

Turn your Acuity Scheduling data into a queryable knowledge base with LlamaIndex. Ask questions, get answers grounded in facts.

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Connect Acuity Scheduling MCP to LlamaIndex

Create your Vinkius account to connect Acuity Scheduling 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 Acuity Scheduling with LlamaIndex

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Index your availability patterns

Build a RAG application that knows your schedule inside and out. Have your LlamaIndex agent periodically call `list_available_times` for key services and index the results. The data becomes part of a long-term memory for your agent. After a few weeks, you can ask questions like, "When are we usually open for consultations on a Monday morning?" Your agent won't need to hit the live API. It will query its own indexed knowledge of your past availability, giving you answers based on historical patterns.

Create a searchable service and product catalog

Use LlamaIndex to build an intelligent catalog of everything you offer. Your agent can run `list_appointment_types`, `list_classes`, and `list_products` one time to populate a vector index. All your services, prices, and durations become instantly searchable. This lets you ask complex questions in natural language. Try asking, "Show me all group classes under $50" or "Do we have any 60-minute services?" Your agent can query its index and give you a precise answer pulled directly from your Acuity Scheduling data.

Analyze historical booking data with this MCP Server

Turn raw booking data into business intelligence. Set up a LlamaIndex agent to regularly fetch data with `list_appointments` and add it to a knowledge base. You're essentially creating a searchable archive of your business activity. This indexed data lets you find trends without constantly hitting the Acuity API. You can query your RAG app for things like "How many new client appointments did we have last month?" or "Which services were most popular in Q4?" and get immediate, fact-based answers.

Setup guide

Set up Acuity Scheduling 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 Acuity Scheduling 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 Acuity Scheduling tools.",
)
response = await agent.run("List recent Acuity Scheduling 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 Acuity Scheduling. 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 Acuity Scheduling MCP in LlamaIndex

By indexing the output of tools like `list_appointments` and `list_classes` over time. This creates a searchable history, letting your LlamaIndex agent answer questions about past booking trends and service popularity.

Yes, the `list_appointments` tool includes a date range filter. You can build your LlamaIndex agent to fetch and index appointments month by month, for example.

It does. Call `list_calendars` to get the IDs for all your providers. You can then use those IDs to filter other queries or build separate knowledge bases for each provider's schedule in your LlamaIndex app.

Yes. The `list_classes` tool returns all scheduled classes, including their capacity and how many people have enrolled. Your agent can use this to see which classes are popular or nearly full.

The server handles appointment details, product lists, and calendar data from Acuity Scheduling. Vinkius ensures each request made by your LlamaIndex agent is processed in a zero-trust environment. The data is not persisted on the MCP server itself.

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