How to Use the DigitalChalk MCP in Mastra AI

Q: Can I require manual approval before Mastra AI modifies DigitalChalk records?

Absolutely. You can configure requireToolApproval on tools like getuserlearningprofile so an administrator must verify the DigitalChalk data before the agent triggers external workflows.

Build resilient, multi-step DigitalChalk automation workflows with Mastra AI and this managed MCP Server.

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Connect DigitalChalk MCP to Mastra AI

Create your Vinkius account to connect DigitalChalk 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 DigitalChalk with Mastra AI

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Automate Learner Escalations with Mastra AI

Stop manual student tracking inside your LMS. This MCP Server lets your Mastra AI agent call `list_recent_course_completions` to trigger automated post-course follow-ups or certificate generation. If an API call to DigitalChalk fails, Mastra's built-in retry mechanism handles the network hiccup. You can build a workflow that checks `get_user_learning_profile` and branches into different email campaigns based on actual student progress.

Branching Workflows for Struggling Students

Identify and support students who are falling behind in their DigitalChalk courses. Your Mastra AI agent can query `list_high_performing_learners` to separate top students from those who need immediate academic help. From there, the workflow can look up specific test scores using `list_assessment_exams`. You can configure a Mastra AI human-in-the-loop approval step before your agent schedules a tutoring session.

Sync Course Offerings Resiliently

Keep your internal databases synced with your active DigitalChalk courses using Mastra AI workflows. The agent queries `list_course_offerings` to grab the latest metadata and maps it to your system. If the connection drops, Mastra retries the request using exponential backoff. You get clean, uninterrupted syncs without writing complex error-handling boilerplate for `get_offering_details`.

Setup guide

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

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

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

Mastra AI manages this out of the box. When your agent calls `list_user_enrollments`, any network error triggers automated backoffs so your DigitalChalk sync workflows don't fail silently.

Absolutely. You can configure `requireToolApproval` on tools like `get_user_learning_profile` so an administrator must verify the DigitalChalk data before the agent triggers external workflows.

The framework queues your tool calls. If your Mastra AI agent is running `list_lms_users` across thousands of accounts, it throttles the requests to stay within DigitalChalk API bounds.

Yes, Mastra AI deploys to any cloud with a single command. The MCP client connects to our hosted endpoint, allowing your workflow to access `get_lms_account_metadata` from any serverless runtime.

Your API tokens are injected securely at runtime and never exposed to the LLM. Vinkius executes the MCP Server code in a zero-trust sandbox, ensuring that sensitive completion records accessed via `list_recent_course_completions` remain private.

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