How to Use the Zephyr Scale (SmartBear) MCP in Vercel AI SDK

Q: Can I use Zephyr Scale (SmartBear) with Vercel AI SDK for status checks?

Yep. You can call tools like listexecutions to get a list of test runs. The streamable nature of the Vercel AI SDK means your UI updates as soon as those execution records come through.

Get real-time test data streaming directly into your UI with Vercel AI SDK.

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Connect Zephyr Scale (SmartBear) MCP to Vercel AI SDK

Create your Vinkius account to connect Zephyr Scale (SmartBear) 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 Zephyr Scale (SmartBear) with Vercel AI SDK

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Check Test Case Details in Real Time

Use `get_test_case` to pull full details for a specific Zephyr Scale (SmartBear) test case. When your agent calls this tool, the resulting data streams immediately into your React or Next.js frontend. Users see the information appear live, without waiting for a loading spinner.

List All Test Environments via MCP Server

The `list_environments` tool provides all available test environments (like Staging and Production). Your AI client fetches this list, and the results are streamed directly into your user interface. This lets you build dynamic UIs that react instantly to environment changes.

Fetch Test Cycles for Dynamic UI Elements

You can use `list_test_cycles` to get all test cycles associated with a project. The returned data streams, letting your agent populate dropdown menus or status cards in real-time within the client's view. It makes building user-facing product views much cleaner.

Setup guide

Set up Zephyr Scale (SmartBear) 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 Zephyr Scale (SmartBear) 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 Zephyr Scale (SmartBear) transactions",
});

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

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Common questions about Zephyr Scale (SmartBear) MCP in Vercel AI SDK

The MCP Server exposes the Zephyr Scale tools, and your Vercel AI SDK client streams the results directly into your front-end. This means when you ask to check test plan details using `get_test_plan`, the data appears instantly in the UI.

Yep. You can call tools like `list_executions` to get a list of test runs. The streamable nature of the Vercel AI SDK means your UI updates as soon as those execution records come through.

Because the results stream directly, it handles larger datasets gracefully. You don't wait for a massive JSON blob; you see chunks of test case or execution status as they become available.

This MCP Server touches test case keys, names, and statuses. The streaming nature ensures that even if you're pulling status updates for multiple test cases using `list_test_cases`, the UI remains responsive.

It is built specifically for building user-facing products. The streamable architecture ensures that your end users see the data from Zephyr Scale (SmartBear) appearing live, which is critical for a professional experience.

Use it with your favorite AI tools

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