How to Use the HackEDU (Security Journey) MCP in Mastra AI

Q: How does HackEDU (Security Journey) work with Mastra AI human-in-the-loop?

You can use the requireToolApproval setting on specific functions. This forces the agent to pause before creating a new issue, letting you review the action first.

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Connect HackEDU (Security Journey) MCP to Mastra AI

Create your Vinkius account to connect HackEDU (Security Journey) 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 HackEDU (Security Journey) with Mastra AI

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Conditional security remediation with Mastra AI

Use `list_issues` to pull in vulnerabilities and set up branching logic in your Mastra workflows. If a high-severity issue appears, the agent automatically triggers `create_issue` to assign training. This automates the boring parts of security management. You define the rules once, and the agent handles the enforcement across your engineering teams.

Automated training assignment via MCP Server

Chain `list_adaptive_training_plans` with your existing issue tracking system. When a developer gets flagged for a specific vulnerability, the agent assigns the relevant training module automatically. It removes the friction between finding a bug and teaching the fix. Your developers get the right content at the exact moment they need it.

Monitor security health with agent workflows

Deploy a scheduled workflow that calls `get_team_progress` to check for stalled training. If a team falls behind, the agent can notify your security leads via Slack or email. It keeps your security culture moving forward. You get proactive alerts instead of waiting for a quarterly compliance audit to find the gaps.

Setup guide

Set up HackEDU (Security Journey) 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 HackEDU (Security Journey) 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: "hackedu-security-journey-mcp-client",
  servers: {
    "hackedu-security-journey-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about HackEDU (Security Journey) MCP in Mastra AI

Add the server to your Mastra configuration file using the MCP transport settings. You can then import the tools directly into your agent definitions for immediate use.

Yes. Mastra supports automatic retries and exponential backoff. If an API call to `list_vulnerabilities` fails due to a network blip, the framework handles the recovery.

You can use the `requireToolApproval` setting on specific functions. This forces the agent to pause before creating a new issue, letting you review the action first.

It does. You can assign different tools to different agents based on their roles. One agent can focus on `list_users` while another handles the remediation logic.

The server returns structured data on training progress, vulnerability taxonomy, and user status. This allows your workflows to make informed decisions about security coverage.

Use it with your favorite AI tools

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