How to Use the Acuity Scheduling MCP in Vercel AI SDK

Q: Can the Vercel AI SDK stream Acuity Scheduling appointment details?

Yes. When your agent calls getappointment, the resulting data streams back to your frontend chunk by chunk. You map those chunks to React components instantly.

Q: How do I filter Acuity Scheduling bookings in Vercel AI SDK?

Pass a date range to the listappointments tool. The agent handles the query parameters automatically based on the user's prompt.

Build live scheduling interfaces. Stream Acuity Scheduling data directly into your React or Next.js frontend using Vercel AI SDK.

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Connect Acuity Scheduling MCP to Vercel AI SDK

Create your Vinkius account to connect Acuity Scheduling to Vercel AI SDK 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 Vercel AI SDK

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Render Live Booking Flows with this MCP Server

Executing `list_available_times` and `check_availability_dates` pulls open slots instantly. Vercel AI SDK streams these available times straight into your Next.js components over the MCP connection. Users see calendar dates light up as the data arrives over the wire. Nobody sits around waiting for a massive JSON payload to finish downloading. Your agent pulls service details via `list_appointment_types` to show pricing and duration right next to the time slots. The user clicks a time, and your interface reacts immediately. That happens because you pipe the MCP client output directly into your text generation functions.

Display Real-Time Class Capacity

Calling `list_classes` grabs current enrollment numbers and total capacity for group sessions. You map that data to a React progress bar component. As the AI reads the Acuity Scheduling response, the UI updates to show empty spots before the full text generation even finishes. Instructors get their own views powered by `list_calendars`. The edge function queries the specific provider's schedule and streams back their daily roster. It keeps your frontend snappy and your users looking at fresh data instead of a frozen screen.

Build Interactive Client Dashboards

The `list_appointments` tool pulls a customer's upcoming bookings based on a date range. You pass that array into a Svelte or Vue table component. When a user asks about their next session, the AI fetches the exact record using `get_appointment` and renders a specialized UI card. Merch and gift cards plug right into the same chat interface. Your agent runs `list_products` to pull available items from Acuity. The user browses physical goods and digital certificates without ever leaving your custom application.

Setup guide

Set up Acuity Scheduling MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Acuity Scheduling tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Acuity Scheduling transactions",
});

console.log(text);
await mcpClient.close();

Get your connection token →

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 Vercel AI SDK

Install @ai-sdk/mcp and the core AI package. Initialize createMCPClient with your Vinkius HTTP endpoint. Pass the resulting tools directly into your streamText call.

Yes. When your agent calls get_appointment, the resulting data streams back to your frontend chunk by chunk. You map those chunks to React components instantly.

Pass a date range to the list_appointments tool. The agent handles the query parameters automatically based on the user's prompt.

The HTTP transport layer works perfectly on the edge. You just need to ensure you call mcpClient.close() when the streaming response completes.

Vinkius runs this integration inside an ephemeral V8 Isolate. Your customer names, phone numbers, and booking histories pass through memory and vanish. We store absolutely nothing.

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