How to Use the PractiTest MCP in Mastra AI

Build reliable QA workflows in Mastra AI by chaining PractiTest operations with automatic retries and conditional logic.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect PractiTest MCP to Mastra AI

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

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Setup PractiTest with Mastra AI

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Orchestrate complex test sequences

Chain `list_tests` and `create_run` within your Mastra agents to build multi-step QA processes. If a test fails to create, the workflow engine handles the logic to retry or alert your team. This setup removes the manual burden of managing test runs. Your agents handle the execution sequence based on the conditions you define in your code.

Resilient test run management

The MCP Server integrates with the Mastra workflow engine to ensure every `create_instance` call is accounted for. If the network blips, the agent retries the operation automatically. You stop worrying about dropped requests or inconsistent data. The agent ensures the run is logged correctly, maintaining the integrity of your project history.

Conditional project reporting

Use `get_project` and `list_requirements` to feed data into your decision-making workflows. Your agents can branch logic based on the specific status of a requirement or test. This builds a smarter feedback loop for your team. The agent acts only when the criteria are met, preventing unnecessary API noise and keeping your logs clean.

Setup guide

Set up PractiTest MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All PractiTest tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "practitest-alternative-mcp-client",
  servers: {
    "practitest-alternative-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "PractiTest Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to PractiTest tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent PractiTest transactions"
);
console.log(result.text);

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Common questions about PractiTest MCP in Mastra AI

Add the MCP Server to your Mastra agent configuration. Once connected, your agents can call tools like create_test or list_runs as part of their defined execution logic.

Mastra handles retries natively for all MCP tool calls. If a request to the server fails, the framework attempts to recover based on your defined policy.

Define steps in your workflow that check project status before calling the run tool. This allows you to skip execution if your requirements are not ready.

You can set tool approval requirements within your agent. This forces a manual check before the server executes sensitive actions like creating new test cases.

The server only reads and writes your project metadata, test definitions, and run status. We keep your credentials isolated and strictly manage access to your QA records.

Use it with your favorite AI tools

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