ContextQA MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect ContextQA through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using ContextQA, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About ContextQA MCP Server
Connect your ContextQA account to any AI agent and take full control of your context-aware AI testing platform through natural conversation.
The Vercel AI SDK gives every ContextQA tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Project & Suite Management — List bounded test environments and perform structural extraction of GUI test suites across your projects
- AI-Healing Executions — Monitor active test runs and inspect specific AI-healing states, including failing step boundaries and screen captures
- Automated Triggers — Dispatch live testing commands to queue suites against ContextQA test clusters directly from your workspace
- API & Swagger Testing — Enumerate automated HTTP assertions and explicitly verify structural payloads against OpenAPI configurations
- Environment Auditing — List physical runtime URLs and group active contexts to verify testing boundaries across different layers
- Test Case Inspection — Resolve AI root-cause models and validate specific case definitions to identify precise points of failure
The ContextQA MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect ContextQA to Vercel AI SDK via MCP
Follow these steps to integrate the ContextQA MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from ContextQA and passes them to the LLM
Why Use Vercel AI SDK with the ContextQA MCP Server
Vercel AI SDK provides unique advantages when paired with ContextQA through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same ContextQA integration everywhere
Built-in streaming UI primitives let you display ContextQA tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
ContextQA + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the ContextQA MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query ContextQA in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate ContextQA tools and return structured JSON responses to any frontend
Chatbots with tool use: embed ContextQA capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with ContextQA through natural language queries
ContextQA MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect ContextQA to Vercel AI SDK via MCP:
get_case
Validate Data Science object extraction tracking explicit steps boundaries
get_execution
Execute static queries targeting exactly specific AI-healing Run states
get_project
Retrieve explicit Project mapping UUIDs analyzing execution spaces limitlessly
list_api_tests
Extracts native REST & OpenAPI testing configurations natively
list_cases
Discover explicit routing limits structuring ContextQA cases trees
list_environments
List static configurations mapping Environment target layers mapping limits
list_executions
Inspect deep internal interaction tracking explicit global Run chunks
list_projects
Identify bounded ContextQA test environments grouping automated validations
list_suites
Perform structural extraction matching asynchronous GUI test Suites payloads
trigger_run
Dispatch a live testing command routing explicit Jobs against pipelines
Example Prompts for ContextQA in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with ContextQA immediately.
"List all test suites for project 'vinkius-app-prod'"
"Trigger a run for suite 'Checkout-Flow' in project 'vinkius-app-prod'"
"Show me why the last execution of project 'mobile-app' failed"
Troubleshooting ContextQA MCP Server with Vercel AI SDK
Common issues when connecting ContextQA to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpContextQA + Vercel AI SDK FAQ
Common questions about integrating ContextQA MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect ContextQA with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect ContextQA to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.