---
title: "LearnDash + Angie"
source: "https://docs.nexcess.com/software/learndash/learndash-angie/"
description: "What Is Angie? Angie by Elementor is a built-in AI assistant that helps site owners manage and create content. For LearnDash users, Angie comes with a hosted MC…"
vertical: "Software"
area: "LearnDash"
date: "2026-02-05"
last_modified: "2026-02-05"
---

# LearnDash + Angie

## **What Is Angie?**

**Angie by Elementor** is a built-in AI assistant that helps site owners manage and create content. For LearnDash users, Angie comes with a **hosted MCP client**, which means it can interact with LearnDash through the REST API without any technical setup.

Angie offers LearnDash users the easiest entry point into MCP-powered AI. With its hosted server, no setup requirements, and built-in Elementor integration, Angie is perfect for educators and site owners who want to manage LearnDash with AI, without worrying about technical steps.

## **Why Use Angie with LearnDash?**

Angie is designed for non-technical users who want to get started quickly. It allows LearnDash users to:

- Create and organize new courses
- Update course settings like start dates, access mode, or pricing
- Assign users to groups or enroll them in courses
- Suggest course structures or lesson layouts based on prompts
- Add tags, categories, and other organizational features

Because Angie is hosted by Elementor, the connection is seamless. Users simply enable Angie, connect LearnDash, and start prompting.

## **Key Benefits of Using Angie**

- **No setup required** – The hosted AI agent is already included.
- **No application password needed** – Authentication is handled automatically.
- **Elementor integration** – Works natively in sites already using Elementor.
- **Beginner-friendly** – Designed for natural language use without technical steps.
- **Safe defaults** – Angie follows the LearnDash API and executes one action at a time.

Note: Even though Angie can act on multiple courses or students, all “bulk” actions are performed one by one. For example, enrolling 10 students means Angie processes 10 separate enrollment actions.

## **How to Connect Angie to LearnDash**

1. **Ensure LearnDash is installed and active** on your WordPress site.
2. **Enable Angie** through the Elementor dashboard or plugin settings.
3. Angie will automatically detect LearnDash and begin offering LearnDash-aware suggestions.
4. Start prompting Angie with natural language requests.

There is no need to generate an application password for Angie’s connection.

## **What You Can Do with Angie**

Here are examples of prompts that work well with Angie:

**Create a New Course**

“Create a new LearnDash course called ‘Science Explorers.’ Set it to free access and make it start on October 1, 2025, and end on December 15, 2025.”

**Add a Lesson with an Assignment**

“Add a new lesson called ‘Final Project’ at the end of the course ‘Science Explorers.’ Enable assignments worth 50 points.”

**Update Course Enrollment Settings**

“Change all courses with access mode ‘buy now’ to access mode ‘closed’ and set their price to unavailable.”

**Organize Content**

“Tag all courses related to AI with the tag ‘Artificial Intelligence’ and assign them to the category ‘Emerging Tech.’”

## **Privacy and Data Access**

When using Angie:

- Prompts flow through **Elementor’s hosted MCP infrastructure,** under Angie’s [Terms and Conditions](https://elementor.com/terms/angie-terms-conditions/).
- LearnDash, Liquid Web, and StellarWP do **not** see any prompts, responses, or data.
- Angie never stores prompts inside LearnDash itself.

For maximum privacy, some users may prefer a **local MCP server** (for example, using Cursor with a local model). Angie, however, is optimized for accessibility and convenience.

## **Developer and Power User Notes**

- Angie’s hosted AI agent cannot be customized.
- Developers who need full control (e.g., local-only models, advanced prompt chaining, or integrations with custom endpoints) should use Cursor with an external MCP server.
- For full technical details on MCP endpoints and developer options, see the[ LearnDash MCP Readme](https://go.learndash.com/mcpreadme).