How to Use the Cloud BOT MCP in OpenAI Agents SDK

Run cloud-based automation tasks directly from your OpenAI Agents SDK production environment.

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Connect Cloud BOT MCP to OpenAI Agents SDK

Create your Vinkius account to connect Cloud BOT 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 Cloud BOT with OpenAI Agents SDK

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Execute remote browser tasks

Trigger headless browser processes by calling `execute_bot` within your agent logic. Your production agent handles the JSON input parameters, allowing for precise control over web navigation and data extraction without writing custom browser drivers. Safety guardrails in your SDK catch malformed inputs before they hit the cloud infrastructure. You get a clean execution flow that lets your agent manage site interactions while staying within your predefined operational constraints.

Manage active job lifecycles

Monitor the health of your automated processes using `get_job_status` to see real-time updates. If a process hangs or hits an unexpected state, use `cancel_job` to kill the task immediately, keeping your agent’s queue clear. You avoid stale tasks clogging your system. It keeps your agent dashboard accurate, showing only the jobs that actually matter to your current operation.

Audit your automated agent storage

Call `list_cloudbot_files` to see every artifact produced by your bots. You get a direct look at the data stored in the Cloud BOT environment, making it easy to pull reports or logs back into your agent’s workspace. Keep your data pipeline tight by referencing only the files you need. This tool gives your agent full visibility into remote storage without manual file handling.

Setup guide

Set up Cloud BOT 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 Cloud BOT tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the necessary dependencies and define your server using the MCPServerStreamableHttp class. Pass your endpoint into the agent constructor and let the SDK handle tool discovery automatically.

Vinkius manages all authentication via a single endpoint token. Your agent never touches raw credentials, keeping your secrets locked away from the runtime environment.

Yes, you can filter the tool list before passing it to the agent constructor. This restricts the agent to only the operations you explicitly authorize.

It does. The implementation relies on async context managers, ensuring your agent remains non-blocking during long-running browser tasks.

The server only touches job metadata and browser-generated output files. We enforce strict isolation so the agent only interacts with the specific job records you provide.

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