Moodle MCP Server and API Server: Universal Adapter for AI Applications

Overview: What is the Moodle MCP Server?

The Moodle MCP (Model Context Protocol) Server is a powerful integration solution that enables AI applications, such as Claude Desktop, Continue, Cursor, and others, to interact with the Moodle platform for course management, student interactions, assignment handling, and quiz administration. By leveraging the openapi specification, this server provides a REST API, ensuring seamless interoperability.

🔧 Core Features & MCP Capabilities

Unified Interface

The Moodle MCP Server offers a unified interface that abstracts complex interactions required with the Moodle platform. With its compatibility matrix, developers can identify which specific tools and resources are supported by various AI clients. The current support includes Claude Desktop, Continue, and Cursor.

Standardized Protocol

MCP adheres to a standardized protocol, enabling multiple AI applications to interoperate seamlessly. This makes it easier for developers and AI enthusiasts to integrate with existing systems without the need for custom development.

REST API Integration

The server integrates with Moodle through an openapi-compliant REST API, facilitating interactions that align with the standard API specifications of other tools.

⚙️ MCP Architecture & Protocol Implementation

Client Interaction Flow

The following Mermaid diagram illustrates how AI applications (MCP clients) interact with the Moodle MCP Server using the MCP protocol:

graph LR;
  A[AI Application] --> B[MCP Client]
  B --> C[MCP Server]
  C --> D[Moodle Platform]
  arrowLabelAngle: -20
  style A fill:#e1f5fe
  style C fill:#f3e5f5
  style D fill:#f5f8ff

Data Flow Architecture

Below is a Mermaid diagram that depicts the data flow architecture, showcasing how data is processed and transmitted from AI applications to Moodle:

graph LR;
    A[AI Application] -->|MCP Request| B[MCP Server]
    B --> C[Moodle Platform]
    C --> D[Database/Back-End Services]
    D --> E[Data Transformation]
    E --> B
  arrowLabelAngle: -20
  style B fill:#f3e5f5
  style C fill:#eeffff
  style D fill:#ecfcff

🚀 Getting Started with Installation

To begin using the Moodle MCP Server, you need to ensure that your local Moodle server is operational. You can either use a remote Moodle server or set up a local one. Below are step-by-step instructions:

Prerequisites

1. Ensure Node.js and pnpm are installed.
2. Install Docker if you plan to run the server via docker.

Installation Command

git pull
pnpm install

Running the Development Environment

To start both the Hono server and MCP server simultaneously, use:

pnpm run dev:all

If you need to build the code before starting, first execute:

pnpm run build 

Then, start the servers using:

pnpm run start

Binary Build for Specific Architectures

To build the server as a binary file using Bun (a fast Node.js runtime), use the following command. This may need to be adjusted based on your specific architecture needs.

pnpm run build:binary

Docker Integration

You can also run the server in a Docker container by setting appropriate environment variables:

docker run \
  -e MOODLE_BASE_URL=https://your.moodle.url \
  -e MOODLE_WSTOKEN=yourtoken \
  -p 3000:3000 \
  -p 6277:6277 \
  moodle-mcp-server

For a real-world example, consider the following command:

docker run \
  -e MOODLE_BASE_URL=https://moodle-27.localcan.dev \
  -e MOODLE_WSTOKEN=0aa2a744e8ccb6c0a9453f432d3659dc \
  -p 3000:3000 \
  -p 6277:6277 \
  moodle-mcp-server

💡 Key Use Cases in AI Workflows

Scenario 1: Automated Grading with Prompt Engineering

AI applications like Claude Desktop can use the Moodle MCP Server to automatically grade student assignments based on predefined prompts. The server's REST API allows for seamless communication between the application and Moodle, ensuring that grading processes are both efficient and accurate.

Implementation:

curl -X POST \
  https://localhost:3000/api/submitAssignment \
  -H 'Content-Type: application/json' \
  -d '{"assignmentId": "123", "studentData": "..."'

Scenario 2: Real-Time Student Analytics for Teachers

Teachers can receive real-time updates on student performance and engagement using the API. The server provides detailed analytics from Moodle, allowing teachers to make informed decisions about teaching strategies.

🔌 Integration with MCP Clients

The following compatibility matrix highlights which AI clients support specific features of the Moodle MCP Server:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

📊 Performance & Compatibility Matrix

This section outlines the key performance and compatibility details of the Moodle MCP Server. It is designed to ensure that developers can integrate with a wide range of AI applications, including those from leading providers such as Claude Desktop, Continue, and Cursor.

Configuration Example

Here’s an example of how you might configure your environment variables within a JSON file for more complex setups:

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "MOODLE_BASE_URL": "https://your.moodle.url",
        "MOODLE_WSTOKEN": "yourtoken"
      }
    }
  }
}

🛠️ Advanced Configuration & Security

The Moodle MCP Server can be configured with various settings to enhance its performance and security. You can set up environment variables or modify the configuration files to suit your needs.

Security Considerations

• Ensure that production deployments use secure communication protocols like HTTPS.
• Regularly update the server software to apply patches and improvements.
• Implement rate limiting and other measures to prevent abuse of the API endpoints.

❓ Frequently Asked Questions (FAQ)

1. How do I integrate multiple AI applications with Moodle?

You can set up the Moodle MCP Server and configure it with different AI clients by adjusting environment variables or through Docker configuration.

2. Are there any known issues running the server in a remote instance?

Remote setup may require additional testing for authentication and connectivity, especially if using self-signed certificates.

3. Can I use this server with other LMS platforms besides Moodle?

Currently, the server is tailored specifically for integrating with Moodle. Extensions or modifications would be required to support different Learning Management Systems (LMS).

4. How does the server handle large volumes of data?

The server is designed to process standard volumes of data typical in educational settings. For extremely high-volume operations, you might need to optimize database configurations or use additional resources.

5. What happens if I make a mistake setting up environment variables?

Properly checking the documentation and ensuring correct values can prevent issues. If problems arise, review logs and consult the help section in the openapi documentation.

👨‍💻 Development & Contribution Guidelines

Contributions to the Moodle MCP Server are welcomed from developers and AI enthusiasts. To contribute, please follow these guidelines:

1. Fork the repository on GitHub.
2. Create a new branch for your feature or bug fix.
3. Commit changes following the conventional commit format.
4. Submit a pull request to the main branch.

🌐 MCP Ecosystem & Resources

Explore additional resources related to MCP and its applications in AI:

• Model Context Protocol Documentation
• GitHub Repository for MCP Server
• Community forums for discussing challenges and best practices.

By leveraging the Moodle MCP Server, developers can build robust integrations that enhance the functionality of AI applications in educational settings.