How to Use the Aero Workflow MCP in OpenAI Agents SDK

Q: How do I connect the OpenAI Agents SDK to Aero Workflow?

You'll instantiate an MCPServerStreamableHttp object with your Vinkius endpoint URL. Then pass it to your Agent constructor in the mcpservers list. The agent discovers all the Aero Workflow tools automatically.

Q: What happens if the Aero Workflow API is down?

The checkapihealth tool will fail, and any other tool call will likely time out or return an error. Your agent's error handling logic will need to manage this, for example, by retrying later or notifying you.

Build production-grade accounting agents with the OpenAI Agents SDK and Aero Workflow. Guardrails included.

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Connect Aero Workflow MCP to OpenAI Agents SDK

Create your Vinkius account to connect Aero Workflow 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 Aero Workflow with OpenAI Agents SDK

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Automate Client and Task Creation

This MCP server connects your agent directly to your Aero Workflow account. You can build agents that automatically create new entries when a trigger fires. Use `create_new_customer` to add a client to your firm's roster or `create_new_workflow_task` to assign work to your team. Because the OpenAI Agents SDK has built-in guardrails, you can review and approve these actions before they run. This prevents your agent from accidentally creating duplicate customers or assigning tasks incorrectly. It's a safety net for production systems.

Give Your OpenAI Agent Direct Access to Aero

Your agent can pull real-time data from your practice management software. Let it `list_firm_customers` to get a client roster or `list_firm_team_members` to see who's on your staff. It can even check task status with `get_task_details`. This gives your specialized agents the context they need to make smart decisions. An agent responsible for reporting can use `list_time_tracking_logs` to build summaries without you having to export a CSV first. All the data is available through simple tool calls.

Check System Health and Integrations

This isn't just for client work. You can build monitoring agents that keep an eye on your setup. The `check_api_health` tool confirms your Aero Workflow instance is responding correctly. Your agent can also get configuration details. Use `list_configured_webhooks` to see what external triggers are set up or `list_checklist_templates` to find standard procedures. It's useful for building agents that manage other agents or audit your workflows.

Setup guide

Set up Aero Workflow 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 Aero Workflow tools at runtime.
3

Create your Agent

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

Run the agent

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

You'll instantiate an `MCPServerStreamableHttp` object with your Vinkius endpoint URL. Then pass it to your `Agent` constructor in the `mcp_servers` list. The agent discovers all the Aero Workflow tools automatically.

Yes, but you handle that logic within your agent's control flow. The OpenAI Agents SDK is designed for handoffs between specialized agents, so you'd typically build smaller agents that only know how to call a few specific tools.

No. The agent is calling the real Aero Workflow API through the MCP server. The data returned is live data from your account, not a guess from the model.

The `check_api_health` tool will fail, and any other tool call will likely time out or return an error. Your agent's error handling logic will need to manage this, for example, by retrying later or notifying you.

This server interacts with your Aero Workflow customer, task, team member, and time tracking data. Vinkius uses ephemeral, sandboxed environments for each request, and your connection is secured by your unique endpoint token. No data is stored long-term.

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