How to Use the ContextQA MCP in Vercel AI SDK

Q: How do I stream ContextQA run states using Vercel AI SDK?

Use getexecution inside your Vercel AI SDK streamText tool call to pipe live ContextQA AI-healing statuses directly to your Next.js frontend.

Q: Can Vercel AI SDK trigger a live ContextQA pipeline test?

Yes, you pass triggerrun into the tools object of createMCPClient to launch ContextQA test jobs directly from Vercel AI SDK prompt commands.

Q: How does Vercel AI SDK map test environments in ContextQA?

The Vercel AI SDK agent calls listenvironments to grab static target layers from ContextQA, which then render instantly in your React components.

Stream real-time test run states and suite evaluations directly to your Next.js frontend with Vercel AI SDK.

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

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Live AI-SDK UI Streams for ContextQA Runs

`get_execution` pulls the exact state of your ContextQA self-healing runs and streams the raw JSON chunks straight to your Vercel AI SDK React UI. Instead of making your users stare at a blank spinner while your ContextQA tests run, this tool feeds the live status updates directly into the Vercel AI SDK text stream. You pull these states by combining `list_executions` with your active Vercel AI SDK streaming edge routes to track ContextQA runs. This means your Next.js frontend displays live debugging progress as ContextQA heals and corrects broken tests under the hood using Vercel AI SDK.

Instant OpenAPI Audits in Your Next.js App

`list_api_tests` extracts your raw ContextQA REST and OpenAPI configurations directly into your Vercel AI SDK TypeScript edge runtime. Your Vercel AI SDK client reads these configurations to compare live API endpoints against your declared ContextQA test suites on the fly. By calling `list_environments`, your Vercel AI SDK agent instantly maps ContextQA target layers and updates your UI component. This lets developers inspect environment-specific ContextQA routing limits in their Vercel AI SDK React apps without waiting for backend polling cycles.

Run ContextQA Suites via Vercel AI SDK Tools

`trigger_run` dispatches live testing commands via the MCP Server directly from a Vercel AI SDK user prompt. When your user clicks "Run Tests" in your Next.js chat interface, this tool executes the ContextQA job and pipes the feedback loop back to the Vercel AI SDK client. Your Vercel AI SDK client connects to the MCP endpoint to run these validations using `list_suites` to extract structural GUI test payloads. This matches the exact ContextQA suite structure to your Vercel AI SDK frontend layout, keeping your test dashboard accurate.

Setup guide

Set up ContextQA 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 ContextQA 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 ContextQA 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 ContextQA. 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 ContextQA MCP in Vercel AI SDK

Use `get_execution` inside your Vercel AI SDK `streamText` tool call to pipe live ContextQA AI-healing statuses directly to your Next.js frontend.

Yes, you pass `trigger_run` into the `tools` object of `createMCPClient` to launch ContextQA test jobs directly from Vercel AI SDK prompt commands.

The Vercel AI SDK agent calls `list_environments` to grab static target layers from ContextQA, which then render instantly in your React components.

Yes, the ContextQA server connects over standard HTTP transport, making it fully compatible with Vercel AI SDK edge runtimes.

Vinkius runs the ContextQA server in a secure sandbox that never stores your OpenAPI payloads or UUIDs. All extracted testing configurations from `list_api_tests` pass directly to your Vercel AI SDK agent and are wiped immediately.

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