How to Use the AcademyOcean MCP in OpenAI Agents SDK

Q: How do I configure OpenAI Agents SDK to discover AcademyOcean MCP Server tools?

You pass the connection string to the MCPServerStreamableHttp constructor and register it in the Agent class. The SDK auto-discovers listcourses and other tools instantly.

Q: How does tracing work when checking AcademyOcean progress with OpenAI Agents SDK?

Every call to getlearnerprogress shows up in your OpenAI developer dashboard. You see the exact payload sent to the AcademyOcean API and the raw response payload.

Q: How do I cache the tool list for faster course lookups?

Set cacheToolsList=True when initializing the server connection. This keeps your agent from refetching tool definitions every time it needs to run listcourses or listlearners.

Build production OpenAI Agents SDK workflows that manage academy learners and track course progress with strict guardrails.

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Connect AcademyOcean MCP to OpenAI Agents SDK

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

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Auto-invite learners with OpenAI Agents SDK safety

Your OpenAI agent uses `invite_learner` to add new hires to your training pipeline. Before the agent triggers the API, the SDK validates the payload to prevent accidental duplicate invites or malformed email addresses. If the agent tries to send an invite to an invalid domain, your built-in guardrails block the call before it hits the network. You trace the entire execution path directly inside your OpenAI dashboard to debug any issues.

Track course progress using specialized agent handoffs

An agent checks user metrics via `get_learner_progress` and hands off the data to an onboarding specialist agent. This multi-agent setup ensures that struggling learners get targeted follow-ups without cluttering your main agent's logic. This MCP Server exposes the raw progress metrics so your agents can calculate completion rates. By caching the tools list on startup, your agent reacts instantly to learner status changes.

Audit your curriculum catalog on demand

Your OpenAI agent reads your active class roster and syllabus by executing `list_courses` and `list_learners`. The agent compares the current enrollment numbers against active courses to flag inactive accounts. Because the MCP connection handles the heavy lifting, your agent maps learners to their respective courses in memory. You get clean, structured outputs without writing custom wrapper code for the AcademyOcean API.

Setup guide

Set up AcademyOcean 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 AcademyOcean tools at runtime.
3

Create your Agent

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

Run the agent

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

You pass the connection string to the `MCPServerStreamableHttp` constructor and register it in the `Agent` class. The SDK auto-discovers `list_courses` and other tools instantly.

Yes, you configure guardrails on the SDK side to intercept the `invite_learner` tool call. This lets you inspect the email address before the agent actually sends the training invite.

Every call to `get_learner_progress` shows up in your OpenAI developer dashboard. You see the exact payload sent to the AcademyOcean API and the raw response payload.

Set `cacheToolsList=True` when initializing the server connection. This keeps your agent from refetching tool definitions every time it needs to run `list_courses` or `list_learners`.

Your AcademyOcean API keys remain inside the Vinkius sandboxed environment. No learner emails or completion percentages are stored on our servers; they pass directly to your OpenAI runtime over encrypted connections.

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