How to Use the Qualified.io MCP in Mastra AI

Q: How do I set up a candidate retry loop using Qualified.io and Mastra AI?

You create a workflow step that triggers scheduleretryassessmentresult when a candidate requests an extension. Mastra AI handles the scheduling and retries the API call if the Qualified.io MCP Server endpoint is temporarily rate-limited.

Q: Can Mastra AI automatically archive old tests using the Qualified.io MCP Server?

Yes, you can build a cron workflow that calls listassessments to find inactive tests. The agent then calls archiveassessment on any test that has not been used in the last six months.

Q: Can we filter candidate results before processing them?

Yes, your agent calls listassessmentresults to fetch the raw data. Mastra AI then filters these results by score or date before passing them to your internal applicant tracking system.

Automate your entire technical screening pipeline with Mastra AI workflows and live test tracking.

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Connect Qualified.io MCP to Mastra AI

Create your Vinkius account to connect Qualified.io 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 Qualified.io with Mastra AI

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Automated cohort onboarding

The `invite_candidates_via_cohort` tool initiates batch testing for large applicant groups within your Mastra AI workflows. This tool runs inside your Mastra agent's state machine to trigger Qualified.io invitations when a candidate moves to the screening phase. If a Qualified.io invitation fails, Mastra AI's built-in retry logic catches the error and executes `invite_candidates` to try an alternative path. You get a resilient Qualified.io pipeline that doesn't drop applicants because Mastra AI handles temporary network blips automatically.

Grade assessments automatically using this MCP Server

The `list_assessment_results` tool pulls the latest candidate submissions for your Mastra AI workflow engine to evaluate. Your Mastra AI agent checks these Qualified.io scores against your hiring benchmarks to decide the next step. If the score passes, the Mastra AI workflow triggers your next interview step; if it falls short, the `terminate_assessment_result` tool closes the Qualified.io file. This Mastra AI automation ensures no candidate gets stuck waiting in your Qualified.io pipeline.

Human-in-the-loop review cycles

The `create_assessment_result_review` tool posts grading feedback directly into the candidate's Qualified.io record via Mastra AI. Your Mastra AI workflow can pause for human approval before finalizing this Qualified.io review. If a recruiter wants to change a grade, the `update_assessment_result_review` tool updates the feedback in Qualified.io instantly. This keeps your external Qualified.io records perfectly mirrored with your internal Mastra AI database.

Setup guide

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

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

const result = await agent.generate(
  "List recent Qualified.io 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 Qualified.io. 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 Qualified.io MCP in Mastra AI

You create a workflow step that triggers `schedule_retry_assessment_result` when a candidate requests an extension. Mastra AI handles the scheduling and retries the API call if the Qualified.io MCP Server endpoint is temporarily rate-limited.

Yes, you can build a cron workflow that calls `list_assessments` to find inactive tests. The agent then calls `archive_assessment` on any test that has not been used in the last six months.

You configure your Mastra workflow step to catch errors from `invite_candidates`. If a call fails, the workflow uses exponential backoff before retrying, or triggers a fallback notification if the email is invalid.

Yes, your agent calls `list_assessment_results` to fetch the raw data. Mastra AI then filters these results by score or date before passing them to your internal applicant tracking system.

All candidate code submissions and test scores are processed inside an isolated V8 sandbox on Vinkius. Your Mastra AI agent connects using a single secure MCP token, ensuring candidate data goes straight to Qualified.io without exposure.

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