How to Use the edX MCP in Mastra AI

Q: How do I configure the edX Alternative in Mastra AI?

Install @mastra/mcp@latest. Instantiate MCPClient with your server URL, then call mcpClient.listTools() to spread the Open edX tools directly into your agent's toolkit.

Q: Does this setup require human approval for edX Alternative updates?

You can require it. Use Mastra's requireToolApproval setting for destructive actions or sensitive updates like updateuserprofile.

Automate student onboarding and grade syncing workflows with Mastra AI and the edX Alternative MCP Server.

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…and any MCP-compatible client

MCP Servers — Included with Plan

Connect edX MCP to Mastra AI

Create your Vinkius account to connect edX 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 edX with Mastra AI

Ask AI about this MCP

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Build resilient enrollment pipelines

Student registration fails when APIs timeout. By hooking this MCP Server into Mastra AI, you get automatic retries with exponential backoff if the `enroll_in_course` tool hits a snag. You can build conditional branches for edge cases. If `list_enrollments` shows a student is already registered, the workflow skips the signup step and moves straight to sending a welcome email.

Sync user data across systems

Keeping your CRM matched with your learning platform is a massive headache. Your agent can run `get_user_profile` on a schedule to check for changes in the student database. When a discrepancy pops up, the workflow executes `update_user_profile` or grabs specific settings with `get_user_preferences`. Mastra handles the error catching if the update request drops.

Automate Mastra AI academic audits

Manually checking who passed and who failed wastes time. You can write a workflow that loops through active classes using `list_courses` and then pulls performance data via `get_course_grades`. The agent inspects individual performance by calling `get_user_grades`. If a student drops below a threshold, Mastra routes that data to a human-in-the-loop approval step before triggering an intervention.

Setup guide

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

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

const result = await agent.generate(
  "List recent edX 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 edX. 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.

Why Choose Vinkius

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Common questions about edX MCP in Mastra AI

Install `@mastra/mcp@latest`. Instantiate `MCPClient` with your server URL, then call `mcpClient.listTools()` to spread the Open edX tools directly into your agent's toolkit.

Yes. Mastra has a built-in workflow engine that automatically retries failed requests. If you pull too many records with `get_course_blocks`, it backs off and tries again.

You can require it. Use Mastra's `requireToolApproval` setting for destructive actions or sensitive updates like `update_user_profile`.

Mastra auto-detects the transport layer. It will connect to the Vinkius endpoint using Streamable HTTP or SSE without you needing to manually configure the headers.

The connection operates on a zero-trust model. When your workflow reads student test scores or course preferences, Vinkius processes the tokens ephemerally so no sensitive academic records sit on disk.

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