How to Use the LearnUpon MCP in OpenAI Agents SDK

Q: How do I configure the LearnUpon MCP Server with the OpenAI Agents SDK?

Initialize the connection by passing MCPServerStreamableHttp to your agent constructor. Install the package using pip install openai-agents and configure the MCP connection using the endpoint URL.

Q: How does the OpenAI Agents SDK handle agent handoffs for LearnUpon?

One agent uses searchusers to find a profile, then passes the validated user ID to a secondary enrollment agent. This modular setup keeps your token usage low and isolates specific API tasks.

Q: Can I search for courses dynamically using this integration?

Yes, the searchcourses tool allows your agent to look up specific modules by name. The agent then retrieves the exact course ID needed for subsequent enrollment steps.

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Connect LearnUpon MCP to OpenAI Agents SDK

Create your Vinkius account to connect LearnUpon 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 LearnUpon with OpenAI Agents SDK

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Automate learner provisioning with OpenAI Agents SDK

The `create_user` tool lets your OpenAI Agents SDK agent provision new LearnUpon learner accounts instantly. Don't waste time manually typing names; your agent checks the active LMS directory via `list_users` first to stop duplicate profiles dead in their tracks. By running these LearnUpon actions through built-in guardrails, the OpenAI Agents SDK verifies the email format before executing. You get raw execution tracing in your OpenAI dashboard, so you can debug any failed LMS API calls without guessing.

Manage course enrollments programmatically

The `enroll_user_in_course` tool assigns specific LearnUpon training modules to users based on their active roles. If a team member changes departments, the OpenAI Agents SDK agent invokes `unenroll_user` to clear outdated LMS assignments. Handoffs between specialized OpenAI Agents SDK agents handle the LearnUpon lifecycle without manual intervention. One agent identifies the user ID using `search_users`, then hands off the enrollment task to a specialized compliance agent.

Track training completion and course catalogs

The `list_courses` tool pulls your current LearnUpon training catalog directly into the OpenAI Agents SDK context. Your agent compares this list against active student progress using `list_enrollments` to identify lagging compliance. This LearnUpon MCP Server runs over a secure streamable HTTP connection to keep your OpenAI Agents SDK agent updated. Turn on tool caching in the SDK to keep latency low when querying large LMS catalogs.

Setup guide

Set up LearnUpon 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 LearnUpon tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate LearnUpon 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="LearnUpon Agent",
            instructions="You have access to LearnUpon 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 LearnUpon. 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 LearnUpon MCP in OpenAI Agents SDK

Initialize the connection by passing `MCPServerStreamableHttp` to your agent constructor. Install the package using `pip install openai-agents` and configure the MCP connection using the endpoint URL.

Yes, you can define input validation rules on your agent before it triggers `enroll_user_in_course` or `unenroll_user`. This prevents the agent from enrolling the wrong user ID during automated sync runs.

One agent uses `search_users` to find a profile, then passes the validated user ID to a secondary enrollment agent. This modular setup keeps your token usage low and isolates specific API tasks.

Yes, the `search_courses` tool allows your agent to look up specific modules by name. The agent then retrieves the exact course ID needed for subsequent enrollment steps.

This integration processes user emails, names, and passwords through an ephemeral V8 sandbox on Vinkius. Your API keys are injected at runtime and never saved to disk, protecting your learner database from exposure.

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