How to Use the EasyPractice MCP in Vercel AI SDK

Stream clinic data directly into your Vercel AI SDK interface to show real-time appointment volume and billing status.

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Connect EasyPractice MCP to Vercel AI SDK

Create your Vinkius account to connect EasyPractice 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 EasyPractice with Vercel AI SDK

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Live clinic activity monitoring

Hook your UI into `quick_clinic_volume_audit` to display current patient flow metrics instantly. Your Vercel AI SDK frontend renders this data as it arrives, replacing static dashboards with live updates. Developers can push appointment summaries to components without extra processing. You get immediate visibility into your daily schedule.

Instant invoice tracking

Connect `list_clinic_invoices` to your app to highlight outstanding payments. The data streams directly into your view, letting users check billing status without waiting for page reloads. This MCP Server handles the data fetch while your client manages the presentation. It keeps the UI snappy and relevant.

Client record management

Use `search_clinic_clients` and `get_client_details` to pull specific profiles when a user asks a question. Your interface shows the exact history needed for informed patient interaction. Data binding happens via the SDK, ensuring your React or Svelte components stay in sync with the EasyPractice database. It turns plain text queries into actionable patient records.

Setup guide

Set up EasyPractice 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 EasyPractice 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 EasyPractice transactions",
});

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

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Common questions about EasyPractice MCP in Vercel AI SDK

You install the MCP package and point the client to your server URL. It bridges the API directly to your frontend code, letting you call clinic tools inside your stream handlers.

Yes. You just invoke the billing tools and pass the output to your components. It works fine for real-time invoice monitoring.

The server uses token-based auth to keep your clinic data private. Your client only sees what you explicitly request through the tool calls.

The server returns an error which your client can catch. You should implement basic retry logic in your frontend code.

It manages client profiles and names. Your client keeps this data ephemeral and only processes it during the active session.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.