How to Use the Moodle MCP in OpenAI Agents SDK

Q: How do I connect the Moodle MCP Server to my OpenAI Agents SDK project?

Install the package with pip install openai-agents and spin up the server. Initialize MCPServerStreamableHttp pointing to your Vinkius endpoint, then pass it directly into your agent's constructor. The SDK auto-discovers tools like getsiteinfo instantly.

Q: How does OpenAI Agents SDK handle Moodle rate limits during bulk actions?

You should set cacheToolsList=True in your SDK configuration to avoid redundant schema lookups. For heavy tasks like running createusers across entire departments, implement rate-limiting logic in your agent's execution loop.

Q: What is the fastest way to verify course setups?

Have your agent call listcourses to locate the target ID, then immediately run getcoursecontents to verify that all modules are loaded. It takes seconds and requires zero manual clicking through the LMS interface.

Automate enrollment and manage course content directly through OpenAI Agents SDK using safe, multi-agent handoffs.

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Connect Moodle MCP to OpenAI Agents SDK

Create your Vinkius account to connect Moodle to OpenAI Agents SDK 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 OpenAI Agents SDK

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Programmatic Course and User Provisioning

Create and configure your LMS environments using the `create_users` and `create_courses` tools with OpenAI Agents SDK. When a new cohort signs up, your agent runs these commands to set up credentials and launch virtual classrooms. This isn't just about running raw commands. The SDK's built-in guardrails validate each payload before execution, meaning your agent won't accidentally trigger a database collision if a username already exists.

Safe Student Enrollment with OpenAI Agents

Update student registration files by running the `get_enrolled_users` and `enrol_users` tools within your OpenAI Agents SDK pipeline. You can query current participants and add new students to specific cohorts based on external triggers. If an agent encounters a registration error, the OpenAI dashboard traces the exact call sequence. This allows you to inspect the payload sent to the MCP Server and fix bad inputs before they hit your production database.

Automated Grade and Assignment Auditing

Monitor student performance metrics using the `get_course_contents` and `get_user_grades` tools via OpenAI Agents SDK. One agent can pull the syllabus and list pending tasks with `list_assignments`, while a grading agent retrieves student scores. Handoff workflows allow you to pass data from a general triage agent to a specialized grading agent. This keeping-it-simple approach reduces token usage during heavy audit runs using this MCP integration.

Setup guide

Set up Moodle MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Moodle tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Moodle tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Moodle tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Moodle Agent",
            instructions="You have access to Moodle tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 OpenAI Agents SDK

Install the package with `pip install openai-agents` and spin up the server. Initialize `MCPServerStreamableHttp` pointing to your Vinkius endpoint, then pass it directly into your agent's constructor. The SDK auto-discovers tools like `get_site_info` instantly.

Yes, you can write an agent that loops through a list of student records and calls `enrol_users` for each one. The SDK's built-in safety constraints allow you to inspect the payload before it runs to avoid duplicate enrollments.

You should set `cacheToolsList=True` in your SDK configuration to avoid redundant schema lookups. For heavy tasks like running `create_users` across entire departments, implement rate-limiting logic in your agent's execution loop.

Have your agent call `list_courses` to locate the target ID, then immediately run `get_course_contents` to verify that all modules are loaded. It takes seconds and requires zero manual clicking through the LMS interface.

All communication between your OpenAI Agents SDK runtime and the MCP Server on Vinkius is encrypted via HTTPS. Sensitive data like passwords passed to `create_users` or scores retrieved from `get_user_grades` never persist in the Vinkius sandbox.

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