How to Use the Moodle MCP in AutoGen

Q: Can AutoGen agents send messages to Moodle users automatically?

Yes, agents can call sendmessage once they agree on the message content. This lets you build consensus-driven workflows where a supervisor agent must approve any outreach.

Q: How is Moodle student grade data protected during AutoGen debates?

Student grades retrieved via getcoursegrades are processed locally within ephemeral runtime environments. No academic records or grade data are saved to disk or used for model training.

Deploy multi-agent AutoGen teams that debate and coordinate student outreach based on real-time Moodle metrics.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Moodle MCP to AutoGen

Create your Vinkius account to connect Moodle to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Moodle with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Coordinate Moodle outreach via AutoGen debate

`send_message` allows your AutoGen agents to execute communication strategies once they reach consensus. The tool transmits direct messages to students after the debate agents agree on the intervention. A tutoring agent might review grades while a compliance agent checks privacy rules, and only when both agree does the system trigger the message. This prevents automated spam and ensures messages are deliberate.

Debate student progress using this MCP Server

This MCP Server exposes `get_course_grades` and `get_course_completion` to provide raw academic metrics to your agent team. These tools feed performance indicators directly into the agent conversation. Your performance agent can analyze these metrics to flag struggling students, while a support agent proposes study plans. This collaborative analysis prevents knee-jerk alerts based on a single low grade.

Audit Moodle courses with AutoGen agents

`get_course_quizzes` and `get_course_workshops` allow your agents to inspect active course structures. These tools pull assessment types and parameters directly from your active classes. One agent can verify syllabus compliance while another checks that all workshops have active grading rubrics. The agents trade findings in the chat before generating a final audit report.

Setup guide

Set up Moodle MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Moodle tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Moodle_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Moodle data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Moodle_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Moodle data")
    print(result.messages[-1].content)

Get your connection token →

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Moodle now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Moodle MCP in AutoGen

You register the server URL with the HTTP transport parameters in your AutoGen configuration. This binds the tools, including `get_courses` and `get_enrolled_users`, directly to your assistant agents.

Yes, agents can call `send_message` once they agree on the message content. This lets you build consensus-driven workflows where a supervisor agent must approve any outreach.

The framework's tool adapter automatically translates the server's schemas into the JSON format that AutoGen expects. This means you do not have to write custom parsers for tools like `get_course_assignments`.

Yes, you can register multiple endpoints to represent different departments or instances. Your agents will route queries to the correct server based on the course list retrieved from `get_courses`.

Student grades retrieved via `get_course_grades` are processed locally within ephemeral runtime environments. No academic records or grade data are saved to disk or used for model training.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript