PractiTest 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 PractiTest through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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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 PractiTest, 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 PractiTest MCP Server
Connect your PractiTest workspaces to any AI agent and empower it to orchestrate the entire QA lifecycle from physical requirements tracing to defect mapping natively via chat conversations.
The Vercel AI SDK gives every PractiTest tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through 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
- Test Cases & Sets — Tell the AI to investigate any Test Case or Test Set, discovering exact preconditions and expected results (
list_tests,get_test,list_sets) - Test Instances & Runs — Retrieve deep execution histories pinpointing exactly which step caused a regression bounding PASSED/FAILED statuses (
list_runs) - Requirements Tracking — Audit physical system compliance extracting arrays dictating QA delivery thresholds (
list_requirements) - Issue Mapping — Find exact Software Defects bound natively to QA traces verifying complex failure logic (
list_issues)
The PractiTest 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 PractiTest to Vercel AI SDK via MCP
Follow these steps to integrate the PractiTest 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 PractiTest and passes them to the LLM
Why Use Vercel AI SDK with the PractiTest MCP Server
Vercel AI SDK provides unique advantages when paired with PractiTest 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 PractiTest integration everywhere
Built-in streaming UI primitives let you display PractiTest 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
PractiTest + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the PractiTest MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query PractiTest in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate PractiTest tools and return structured JSON responses to any frontend
Chatbots with tool use: embed PractiTest capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with PractiTest through natural language queries
PractiTest MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect PractiTest to Vercel AI SDK via MCP:
get_set
Get full details of a PractiTest test set including name, status, instances count, and execution summary
get_test
Get full details of a PractiTest test case including name, description, preconditions, steps, expected results, custom fields, and requirement links
list_custom_fields
List all custom fields in a PractiTest project. Returns field names, types, applicable entities, and possible values
list_instances
List all test instances in a PractiTest test set. Instances are test-set-specific copies of test cases. Returns instance IDs, test references, and last run statuses
list_issues
List all issues (defects) in a PractiTest project. Returns issue names, statuses, severities, and linked test references
list_requirements
List all requirements in a PractiTest project. Requirements provide traceability to test cases and defects. Returns names, statuses, and linked test counts
list_runs
List all runs for a PractiTest test instance. Runs record actual test execution results. Returns run IDs, statuses (PASSED/FAILED/BLOCKED/NOT_RUN/N_A), durations, and timestamps
list_sets
List all test sets in a PractiTest project. Test sets group test instances for execution. Returns set names, statuses, planned/actual dates, and assigned testers
list_tests
List all test cases in a PractiTest project. PractiTest is an end-to-end test management platform with traceability from requirements to defects. Returns test names, IDs, statuses, custom fields, and traceability links. Uses JSON:API format
list_users
List all users in the PractiTest account. Returns user names, emails, roles, and statuses
Example Prompts for PractiTest in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with PractiTest immediately.
"List all tests inside our active QA regression instance and find the ones mapped as failed."
"Do we have any new custom fields we should be aware of inside the requirements area?"
"Are there any open defects (issues) linked directly to testing scenarios surrounding multi-currency operations?"
Troubleshooting PractiTest MCP Server with Vercel AI SDK
Common issues when connecting PractiTest to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpPractiTest + Vercel AI SDK FAQ
Common questions about integrating PractiTest 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 PractiTest 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 PractiTest to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.