How to Use the BlazeMeter MCP in Vercel AI SDK

Q: How do I trigger a BlazeMeter test using Vercel AI SDK?

Import the tool into your generateText call and execute starttest. The SDK handles the streaming response so you can show the test ID to your user immediately.

Q: Can I see BlazeMeter reports in my Vercel AI SDK frontend?

Yes, pass getreport to your agent tools. The resulting data arrives as a JSON object that you can map directly to charts in your UI.

Q: Does the server handle multiple BlazeMeter projects?

It does. Use listprojects to fetch all available workspaces and filter them based on your current application context.

Stream load test metrics directly into your Vercel AI SDK interface for real-time performance insights.

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Connect BlazeMeter MCP to Vercel AI SDK

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

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Watch BlazeMeter tests run in your UI

Feed live test results straight into your React components. When you call `start_test`, the data streams back through the SDK so your users see progress bars update instantly. Stop waiting for spinners to finish. Use `get_report` to push live arrays into your frontend state so the interface reflects the actual load generation impact immediately.

Manage your BlazeMeter infrastructure

Keep your workspace clean by using `list_projects` and `list_workspaces` inside your application logic. It gives you a clear view of where your data lives without leaving your code editor. This MCP Server handles the heavy lifting of connection management. You just call `list_tests` to show users exactly what is configured and ready for execution.

Control test execution from your app

Trigger specific validation checks by calling `get_master` directly from your event handlers. It allows your application to report on gateway status without manual intervention. Shut down runaway tasks using `stop_master` whenever an anomaly appears. You maintain total control over your environment directly from the user-facing dashboard.

Setup guide

Set up BlazeMeter 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 BlazeMeter 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 BlazeMeter transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by BlazeMeter. 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 BlazeMeter MCP in Vercel AI SDK

Import the tool into your generateText call and execute `start_test`. The SDK handles the streaming response so you can show the test ID to your user immediately.

Yes, pass `get_report` to your agent tools. The resulting data arrives as a JSON object that you can map directly to charts in your UI.

Your credentials and load test configurations never leave the secure Vercel environment. We treat your API tokens as sensitive environment variables.

It does. Use `list_projects` to fetch all available workspaces and filter them based on your current application context.

The server returns the specific error code from the API. You can catch this in your catch block and display the failure reason to the user.

Use it with your favorite AI tools

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