How to Use the Moodle MCP in Mastra AI

Q: How do I add the Moodle MCP Server to a Mastra AI workflow?

Install the package with npm install @mastra/mcp@latest and initialize the client using your Vinkius URL. Then, call mcpClient.listTools() and spread them into your Mastra Agent's tools array. This gives your agent immediate access to course management functions.

Q: How do I approve Moodle course creation in Mastra AI?

Use Mastra's requireToolApproval feature on the createcourses tool. The workflow pauses and alerts your admin, who must approve the action before the MCP Server writes the new course to your database.

Q: Can I build multi-step LMS workflows using Mastra AI?

Yes, you can chain tools like createusers and enrolusers sequentially. Mastra handles the data flow between these steps, ensuring the user is created before the enrollment is attempted.

Build resilient Moodle workflows with Mastra AI to automate student enrollment and handle API retries out of the box.

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Connect Moodle MCP to Mastra AI

Create your Vinkius account to connect Moodle 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 Moodle with Mastra AI

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Resilient student enrollment pipelines with Mastra AI

The `enrol_users` tool adds students to their classes, but network hiccups can sometimes drop the connection. Mastra AI solves this by wrapping this MCP Server tool in a workflow engine with built-in exponential backoff. If the LMS database locks up during peak hours, the system automatically retries the enrollment until it succeeds. You define these steps in clean TypeScript using the `MCPClient` constructor. If a student registration fails repeatedly, the workflow branches to notify your IT staff instead of failing silently. This keeps your enrollment database clean and ensures no student gets left out of their course.

Automated course creation with human approval

The `create_courses` tool creates new learning spaces, but you might want to review them before they go live. Mastra AI provides a `requireToolApproval` gate that pauses the workflow before creating the course. Your agent drafts the syllabus using `list_categories`, prepares the shell, and waits for your thumbs up before writing to the database. This human-in-the-loop pattern keeps your LMS organized without manual data entry. Once you approve the draft, the workflow resumes and executes the creation command instantly. It is the perfect balance of automation and quality control for busy academic departments.

Conditional grading workflows using this MCP Server

The `get_user_grades` tool tracks academic performance, allowing you to trigger targeted interventions automatically. Mastra's workflow engine evaluates the grade output and executes conditional branches based on the score. If a student's grade falls below a threshold, the workflow can query `list_assignments` to find remedial resources. This automation runs entirely in the background without constant manual monitoring by instructors. You write the logic once, and Mastra coordinates the tools to support struggling students. It turns raw gradebook data into active, helpful communication.

Setup guide

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

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

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

Install the package with `npm install @mastra/mcp@latest` and initialize the client using your Vinkius URL. Then, call `mcpClient.listTools()` and spread them into your Mastra Agent's tools array. This gives your agent immediate access to course management functions.

Yes, Mastra's built-in retry logic manages API timeouts when calling `enrol_users`. If your LMS server is busy, the workflow backs off and retries, preventing lost registrations.

Use Mastra's `requireToolApproval` feature on the `create_courses` tool. The workflow pauses and alerts your admin, who must approve the action before the MCP Server writes the new course to your database.

Yes, you can chain tools like `create_users` and `enrol_users` sequentially. Mastra handles the data flow between these steps, ensuring the user is created before the enrollment is attempted.

The MCP Server handles student grades securely inside Vinkius's zero-trust sandbox. No grades are cached or stored on the Mastra side, keeping your student records compliant with privacy standards.

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