How to Use the eduMe MCP in Mastra AI

Q: Can I use Mastra workflows to find inactive trainees?

Yes, you can design a workflow that starts with searchtraineesbykeyword. The agent then inspects each profile to flag accounts that have not completed their assigned courses.

Build resilient mobile training workflows in Mastra AI using eduMe MCP tools.

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Connect eduMe MCP to Mastra AI

Create your Vinkius account to connect eduMe 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 eduMe with Mastra AI

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Automate training remediation in Mastra AI workflows

When a user falls behind, Mastra AI can trigger a multi-step recovery workflow. The agent checks progress using `get_user_training_profile` and decides whether to assign new material. You can write logic that branches based on completion rates. If the trainee hasn't finished their modules, the workflow automatically schedules a follow-up check.

Audit team progress using this MCP Server

Monitoring large groups requires reliable background execution. This MCP Server lets your Mastra agents run scheduled checks across all your user segments. The agent pulls group structures with `list_training_teams` and runs `quick_team_training_audit` to find inactive groups. Mastra handles any API rate limits automatically with built-in retries.

Sync training content updates without manual scripts

Keeping your internal database aligned with your mobile courses is tedious. Mastra agents can poll `list_latest_training_content` to find newly published modules. Once a new course is found, the agent retrieves the full syllabus via `get_course_details`. It then updates your system records without requiring human intervention.

Setup guide

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

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

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

Instantiate the client pointing to your endpoint. Retrieve the tools using the list helper and spread them directly into your agent configuration.

Mastra has built-in exponential backoff. If tool calls like `list_trained_users` hit rate limits, the framework retries the call automatically until it succeeds.

Use the tool approval setting in Mastra. This pauses the workflow before the agent can query sensitive operations like fetching full user profiles.

Yes, you can design a workflow that starts with `search_trainees_by_keyword`. The agent then inspects each profile to flag accounts that have not completed their assigned courses.

Your account metadata and user training history are protected by Vinkius's zero-trust MCP architecture. We isolate every tool execution in an ephemeral sandbox to prevent unauthorized access.

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