How to Use the Didacte MCP in Mastra AI

Q: How do I add the Didacte MCP Server to a Mastra AI agent?

Install @mastra/mcp and instantiate the MCPClient with your Vinkius URL. Call mcpClient.listTools() and spread them directly into your Mastra agent's tool configuration array.

Q: How do I implement human approval for Didacte enrollment changes in Mastra AI?

Use Mastra's requireToolApproval setting on tools like listcourseenrollments. This pauses the workflow and alerts an administrator before the agent proceeds with enrollment updates.

Q: Can I fetch account usage limits using this integration?

Yes. The getaccountmetadata tool retrieves your organization's limits and metadata. Your agent can use this to monitor resource usage and alert you before you hit system boundaries.

Automate LMS workflows and student progress tracking in Mastra AI using the Didacte MCP server.

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Connect Didacte MCP to Mastra AI

Create your Vinkius account to connect Didacte 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 Didacte with Mastra AI

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Manage organization users via Mastra AI

The `list_organization_users` tool exposes your entire Didacte learner roster to Mastra AI workflows. You can build automated steps that check this list, identify new team members, and prepare their learning paths. If a user registration fails, Mastra's built-in retry engine handles the network hiccup with exponential backoff. This ensures your Didacte user management workflows run reliably without manual intervention.

Automate enrollment verification

The `list_user_enrollments` tool retrieves all active classes for a specific learner within a Mastra AI agent loop. Your agent uses this Didacte data to confirm whether a user has access to required training modules. When combined with `get_course_details`, the Mastra AI agent can verify if a Didacte course is still open for enrollment. This lets you build branching logic that automatically redirects students to alternative courses if a class is full.

Monitor learning progress with this MCP Server

The `list_active_learning_progress` tool detects which learners have recently interacted with their Didacte courses. Your Mastra AI agent polls this tool to identify students who might be stuck or falling behind. You can set up a human-in-the-loop approval step using `requireToolApproval` before the Mastra AI agent sends nudges. This keeps an admin in control while automating the tracking of Didacte learner outcomes.

Setup guide

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

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

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

Install `@mastra/mcp` and instantiate the `MCPClient` with your Vinkius URL. Call `mcpClient.listTools()` and spread them directly into your Mastra agent's tool configuration array.

Yes. Mastra AI features automatic retries with exponential backoff, which prevents failures when tools like `list_lms_courses` or `list_course_curriculum` hit API rate thresholds.

Use Mastra's `requireToolApproval` setting on tools like `list_course_enrollments`. This pauses the workflow and alerts an administrator before the agent proceeds with enrollment updates.

Yes. The `get_account_metadata` tool retrieves your organization's limits and metadata. Your agent can use this to monitor resource usage and alert you before you hit system boundaries.

Your account metadata and user directories are shielded by Vinkius's zero-trust sandbox architecture. The MCP server runs in isolated environments, and all API calls to the Workleap endpoint use secure, ephemeral tokens.

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