How to Use the PractiTest MCP in Vercel AI SDK

Stream PractiTest data directly into your Vercel AI SDK interface so users see test results and run status updates in real-time.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect PractiTest MCP to Vercel AI SDK

Create your Vinkius account to connect PractiTest to Vercel AI SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup PractiTest with Vercel AI SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Real-time project visibility

Feed live PractiTest data into your frontend by hooking the MCP Server directly into your stream. Your UI renders test counts and project metadata immediately as `list_projects` and `list_tests` return results. Stop waiting for spinners. Users see the actual state of their QA environment the moment the AI finishes the request, keeping your interface snappy and responsive.

Automate test execution flows

Trigger `create_test` and `create_run` calls directly from your chat components. Your application handles the logic, sending the data payload to the server without forcing the user to switch tabs. Every run logged via `create_run` appears in the UI instantly. You maintain full control over the data flow while the AI handles the heavy lifting of recording results.

Dynamic requirement tracking

Query specific requirements with `get_requirement` and display them alongside live test results. This connection ensures your users are always looking at the latest project specs. Data binding is clean and predictable. By passing tool results into your components, you keep the user context tight and focused on the task at hand.

Setup guide

Set up PractiTest 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 PractiTest 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 PractiTest transactions",
});

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

Get your connection token →

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Why Choose Vinkius

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

Connect PractiTest 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 PractiTest MCP in Vercel AI SDK

Install the MCP package and initialize the client using your Vinkius endpoint. You then pass the tool definitions directly into your generateText function to start executing commands.

Yes. Because the MCP Server streams results, your React components can consume these outputs immediately. This keeps your interface in sync with your QA project state.

It does. You can trigger test runs and see the confirmation status appear in your chat window as soon as the API confirms the write operation.

You can select exactly which tools you want to expose to your agent. This ensures your app only has access to the specific functions it needs for your current workflow.

All communication between your client and our servers is encrypted and ephemeral. We only touch your test cases and run logs, ensuring your sensitive QA metadata stays private.

Use it with your favorite AI tools

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

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