How to Use the Arize AI MCP in Vercel AI SDK

Q: How do I query Arize AI traces using Vercel AI SDK?

Use the listspans tool within your streamText call. It fetches trace data and sends it directly to your frontend components.

Q: Can Vercel AI SDK handle Arize AI dataset creation?

Yes. Call the createdataset tool inside your server-side logic to initialize new datasets based on user input.

Q: How do I list projects in Arize AI from my code?

Invoke the listprojects tool. It returns an array of your active projects for use in your application UI.

Stream Arize AI model performance data directly into your Vercel AI SDK frontends for live observability.

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Connect Arize AI MCP to Vercel AI SDK

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

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Real-time model monitoring in AI SDK

Pipe live prediction quality metrics into your React components using `get_model`. You get raw model metadata pushed straight to the browser without waiting for backend roundtrips. Your UI updates as the data arrives. It replaces stale status pages with a live view of your model's health.

Manage Arize AI datasets via AI SDK

Trigger `create_dataset` or pull `list_datasets` directly from your Edge Functions. It handles the heavy lifting of data organization while your frontend stays responsive. Developers keep the logic tight. You call these tools inside your streamText functions to feed observation data into your user-facing interfaces.

Trace prediction spans in AI SDK

Query specific inference traces with `list_spans` to see exactly why a model produced a certain result. It brings the debugging process into your development environment. This MCP server gives your code eyes on production data. You see the span details as they happen in your terminal or dashboard.

Setup guide

Set up Arize AI 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 Arize AI 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 Arize AI 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 Arize AI. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Arize AI now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Arize AI MCP in Vercel AI SDK

Use the `list_spans` tool within your streamText call. It fetches trace data and sends it directly to your frontend components.

Yes. Call the `create_dataset` tool inside your server-side logic to initialize new datasets based on user input.

It does. Connect via the HTTP transport to ensure low-latency data access during your server-side execution.

Invoke the `list_projects` tool. It returns an array of your active projects for use in your application UI.

The server only touches your Arize AI model metadata and prediction logs. Your credentials stay local to your Vercel environment.

Use it with your favorite AI tools

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

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