How to Use the Global Wine Score MCP in Vercel AI SDK

Q: What happens to the wine data once my Vercel AI SDK session ends?

The session is ephemeral. Once you call mcpClient.close(), the connection terminates and no state is stored on the server side.

Stream real-time wine data directly into your React or Next.js app with this Global Wine Score MCP Server for the Vercel AI SDK.

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Connect Global Wine Score MCP to Vercel AI SDK

Create your Vinkius account to connect Global Wine Score 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 Global Wine Score with Vercel AI SDK

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Live streaming of normalized wine ratings

Feed your UI with live data as your agent processes it. By using `get_latest_scores`, the data pipes straight into your frontend components without waiting for background batch jobs. Your users see the scores appear as the stream finishes. It keeps the interface snappy and responsive while the AI client handles the heavy lifting in the background.

Instant discovery with search tools

Stop guessing which vintage or region performed well. Connect `search_wine_scores` to your input fields to give users immediate feedback on any bottle they query. It handles the heavy lifting of normalization behind the scenes. Your app gets a clean, consistent score out of 100 every single time.

Context-aware wine investment analysis

Use `scores_by_vintage` or `scores_by_country` to build custom dashboards that track market trends. The AI client filters the noise so your users only see the top-rated bottles. These tools turn raw, scattered critic data into actionable lists. It is the fastest way to build a professional-grade wine tracker in your own stack.

Setup guide

Set up Global Wine Score 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 Global Wine Score 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 Global Wine Score 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 Global Wine Score. 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 Global Wine Score MCP in Vercel AI SDK

Install the MCP client packages and point your transport to the Vinkius endpoint. You then pass the tools directly into your `generateText` or `streamText` calls to make them available to your agent.

Yes. The tools return structured JSON that maps perfectly to your TypeScript interfaces. You get the normalized score, vintage, and region data ready for display.

The server provides the most recent data available from the registry. When your agent calls the tools, it fetches the current consensus score for the requested wine.

Vinkius handles the connection via a single endpoint token. Your AI client only sees the wine data you explicitly request through the tools, keeping your environment isolated.

The session is ephemeral. Once you call `mcpClient.close()`, the connection terminates and no state is stored on the server side.

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