How to Use the Acuity Scheduling Alternative MCP in LlamaIndex

Q: Does the Acuity Scheduling Alternative support semantic search out of the box in LlamaIndex?

The server provides the raw data via tools like getappointment. LlamaIndex handles the embedding and indexing, allowing you to run semantic search over your entire calendar history.

Q: How do I prevent the agent from hallucinating free slots?

Force the agent to call getavailability immediately before confirming any slot. By grounding the agent's context in real-time API responses, you eliminate outdated index data.

Index live calendar data into LlamaIndex to query your schedules, availability, and bookings using semantic search.

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Connect Acuity Scheduling Alternative MCP to LlamaIndex

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

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Index active bookings for RAG

Stop writing custom SQL queries to search your schedule. This MCP server lets you pull raw booking data using `list_appointments` and index it straight into your vector store. Your LlamaIndex agent can then answer natural language questions about who is booked when. The agent searches past bookings to find patterns or conflicts. It queries your calendar data directly, combining static documents with live results from `get_appointment` to give grounded answers.

Query real-time availability with LlamaIndex

Keep your search index fresh with live booking slots. Your agent runs `get_availability` to fetch open slots, indexing them dynamically so users can search for free times using plain English. This prevents booking conflicts before they happen. Because LlamaIndex updates its context with live data from `list_calendars`, the agent always knows which slots are genuinely open.

Structural metadata extraction

Organize your calendar by indexing appointment types. Your agent pulls categories using `list_categories` and `list_appointment_types` to build a structured metadata index. This lets your agent filter search results by service type. If a user asks for a specific consultation, LlamaIndex routes the query only to the relevant calendars.

Setup guide

Set up Acuity Scheduling Alternative 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 Alternative 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 Alternative tools.",
)
response = await agent.run("List recent Acuity Scheduling Alternative data")

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Common questions about Acuity Scheduling Alternative MCP in LlamaIndex

You use the LlamaIndex MCP tool spec to connect to the server. The tool outputs from `list_appointments` can then be loaded directly into your document pipeline or vector index.

Yes, the agent isn't limited to reading data. It can use tools like `create_appointment` or `reschedule_appointment` to modify schedules based on user queries.

The server provides the raw data via tools like `get_appointment`. LlamaIndex handles the embedding and indexing, allowing you to run semantic search over your entire calendar history.

Force the agent to call `get_availability` immediately before confirming any slot. By grounding the agent's context in real-time API responses, you eliminate outdated index data.

Client names, email addresses, and appointment times are processed strictly in transit. The Vinkius MCP sandbox ensures no scheduling payloads are logged or stored on disk, keeping your customer data private.

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