How to Use the edX MCP in AutoGen

Q: How is student enrollment data protected during agent execution?

Your enrollment records retrieved by listenrollments are processed in ephemeral, isolated V8 sandboxes. No enrollment history or student identifiers are stored on the host, ensuring compliance with privacy standards.

Deploy multi-agent AutoGen teams to debate grading policies, manage enrollments, and update user profiles automatically.

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Connect edX MCP to AutoGen

Create your Vinkius account to connect edX to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup edX with AutoGen

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Coordinate Multi-Agent Enrollment Workflows

The `enroll_in_course` tool allows your AutoGen agents to execute registrations after reaching consensus on student eligibility. One agent checks prerequisites using `list_enrollments` while another verifies capacity before initiating the sign-up. This multi-agent debate ensures that no student is registered for a course they aren't prepared for. The MCP connection handles the underlying API calls, leaving your agents to focus on the business logic of enrollment validation.

Audit Student Performance via Agent Consensus

The `get_user_grades` tool retrieves individual performance metrics for your specialized auditing agents to analyze. An academic agent flags struggling students while a support agent drafts personalized recovery plans based on the grade data. They cross-reference these findings with `get_course_grades` to determine if a specific assignment is causing issues across the entire cohort. This collaborative analysis produces highly targeted interventions without human intervention.

Manage Profile Settings with AutoGen MCP Server Tools

The `update_user_profile` tool lets an administrative agent modify student records once a verification agent approves the changes. The agents query the current state using `get_user_profile` to ensure they only update modified fields. If preferences conflict, the agents use `get_user_preferences` to resolve the discrepancy before committing the write. AutoGen's schema adapter translates these tool definitions automatically, making them immediately available to the entire agent group.

Setup guide

Set up edX 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 edX 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="edX_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent edX 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="edX_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent edX 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 edX. 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 edX MCP in AutoGen

You register the server using the AutoGen MCP extension and pass the tool list to your assistant agents. This allows agents to cooperatively call `list_courses` or `get_course_details` during their conversations.

Yes. The server handles concurrent requests from different agents executing `enroll_in_course` or `get_user_grades`. The agents can divide tasks, such as one fetching profiles while another checks grades.

Building custom tools requires defining JSON schemas and transport layers for each endpoint. This MCP Server exposes 10 structured tools out of the box, letting your AutoGen agents interact with the platform immediately.

The server supports both stdio and streamable HTTP transports. Deploy it locally for development or connect to our managed endpoint for production agent workflows.

Your enrollment records retrieved by `list_enrollments` are processed in ephemeral, isolated V8 sandboxes. No enrollment history or student identifiers are stored on the host, ensuring compliance with privacy standards.

Use it with your favorite AI tools

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

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