How to Use the NetEase BUFF MCP in Vercel AI SDK

Q: How do I show NetEase BUFF price history in my Next.js app with the Vercel AI SDK?

Call the getpricehistory tool within streamText. The Vercel AI SDK will stream the results, which you can then parse and render into a chart component like Recharts or Chart.js.

Q: Is it possible to track my NetEase BUFF inventory in real-time using the Vercel AI SDK?

Absolutely. Use the getuserinventory tool to fetch and display the items. For updates, you can periodically call syncinventory to refresh the data from Steam's servers.

Build streaming price tickers and live inventory dashboards for NetEase BUFF with the Vercel AI SDK.

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Connect NetEase BUFF MCP to Vercel AI SDK

Create your Vinkius account to connect NetEase BUFF 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 NetEase BUFF with Vercel AI SDK

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Stream BUFF Market Data Live

The `get_price_history` tool streams transaction data directly into your UI. Your users see price charts and order books populate in real-time, without a loading spinner. It's the difference between a static page and a live trading desk. Combine this with `get_sell_orders` and `get_buy_orders` to build a complete market view. Since the Vercel AI SDK streams tool results, you can render new sell listings as they appear. This makes your app feel responsive and alive, not like a simple data fetch.

Build Interactive Inventory UIs

Use the `get_user_inventory` tool to instantly load a user's items into your Next.js or Svelte app. The data streams in, so even large inventories appear piece by piece, not all at once after a long wait. From there, your UI can trigger other tools. A user clicks "Sell," and your agent calls `create_buy_order` with the correct item ID. Connect your frontend directly to market actions on this MCP Server.

Connect Your Frontend in Minutes

Getting started is straightforward. Just `npm install ai @ai-sdk/mcp` and use `createMCPClient` to point at your Vinkius endpoint. The tools from this MCP Server are then ready to be passed into `generateText` or `streamText`. There's no complex backend to manage. You can run these calls directly from your frontend or deploy them to Edge Functions. The AI SDK handles the connection, and Vinkius manages the server, so you can focus on building the UI.

Setup guide

Set up NetEase BUFF 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 NetEase BUFF 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 NetEase BUFF 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 NetEase BUFF. 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 NetEase BUFF MCP in Vercel AI SDK

Call the `get_price_history` tool within `streamText`. The Vercel AI SDK will stream the results, which you can then parse and render into a chart component like Recharts or Chart.js.

Yes. In your component's event handler, have your AI client call the `create_buy_order` tool with the item's details. The order is placed programmatically via the API.

Absolutely. Use the `get_user_inventory` tool to fetch and display the items. For updates, you can periodically call `sync_inventory` to refresh the data from Steam's servers.

The Vinkius endpoint includes a secure token. You pass this URL when you initialize `createMCPClient`, and it's the only secret you need to manage.

This server processes your BUFF market data, like your inventory list and transaction history. Vinkius isolates each request in a sandbox, and your Vercel AI SDK connection is secured by your endpoint token. We don't store your trading data.

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