How to Use the AutoGen MCP in OpenAI Agents SDK

Build production-grade multi-agent systems with AutoGen and the OpenAI Agents SDK.

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Connect AutoGen MCP to OpenAI Agents SDK

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

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Define agent roles in OpenAI Agents SDK

Use `create_agent` to build specialized roles within your swarm. You define the logic and let the SDK handle the heavy lifting of agent-to-agent communication. Your agents operate with strict guardrails. This MCP Server ensures your configurations adhere to the constraints you set in your Python deployment.

Manage workflows for OpenAI Agents SDK

Call `list_workflows` to see exactly what your agent swarm is capable of right now. It pulls the current definitions so your code knows what paths are available. Trigger a new process using `create_message` to keep your agents moving. You get full visibility into the execution chain directly through your dashboard.

Session control via OpenAI Agents SDK

Start fresh by calling `create_session` whenever you need a clean slate for your testing. It wipes the state so you don't carry over old junk. Keep your memory footprint low by using `delete_session` once a task completes. It removes stale data from the server instantly.

Setup guide

Set up AutoGen 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 AutoGen tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate AutoGen 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="AutoGen Agent",
            instructions="You have access to AutoGen tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about AutoGen MCP in OpenAI Agents SDK

Pass the server instance directly into your Agent constructor. The SDK automatically discovers all available tools.

Yes. You can chain multi-agent workflows using the provided toolset. Each agent handles specific sub-tasks within your defined scope.

It does. Every action is checked against your defined schemas before the agent executes the call.

Logs live within the specific session created on the server. You can pull them using the list tools.

Your session history stays inside the isolated Vinkius sandbox. We only touch the message strings required to process your agent's current state.

Use it with your favorite AI tools

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