How to Use the MaestroQA MCP in Mastra AI

Build resilient support workflows in Mastra AI by connecting your agents to live MaestroQA performance data and evaluation rubrics.

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Connect MaestroQA MCP to Mastra AI

Create your Vinkius account to connect MaestroQA to Mastra AI 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 MaestroQA with Mastra AI

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Agent-driven QA workflows in Mastra AI

Automate your review pipeline by using `list_qa_rubrics` to inform agent decision-making. Your workflows now have the context needed to evaluate ticket quality against existing standards. Define conditional branches in your code that trigger actions based on the output of `get_ticket_qa_details`. This removes manual guesswork from your support operations.

Mastra AI agent performance tracking

Use `list_qa_agents` to monitor your team's output within your automated workflows. You can cross-reference these identities with historical ticket data to identify coaching gaps. Your agents can now fetch specific performance snapshots automatically. This creates a feedback loop that adjusts your support strategy based on actual outcomes.

Reliable data syncing for Mastra AI

Push metrics back to your system using `push_csat_scores` to ensure your data stays consistent. The workflow engine manages the retries if the network hits a snag. You keep your audit logs accurate without building custom middleware. Everything stays within your defined control flow.

Setup guide

Set up MaestroQA 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 MaestroQA 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: "maestroqa-mcp-client",
  servers: {
    "maestroqa-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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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 MaestroQA. 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 MaestroQA MCP in Mastra AI

Import the MCP client into your Mastra agent definition and add the server URL. The agent will then automatically detect and list the available tools for your orchestration logic.

You can build a workflow that fetches ticket details and evaluates them against rubrics. If a score hits a certain threshold, the agent can then perform follow-up tasks.

Yes, you can require manual approval before your agent executes any tool. This ensures that sensitive operations like pushing scores or requesting exports remain under your oversight.

The framework supports automatic retries with exponential backoff. This keeps your QA pipeline running even if the platform experiences minor connectivity issues.

All agent and ticket information is processed through an isolated sandbox. We ensure that your sensitive performance metrics never leak outside your configured server environment.

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