How to Use the Vultr MCP in OpenAI Agents SDK

Q: Does Vultr support listing multiple backups with OpenAI Agents SDK?

Absolutely. The agent provides the listbackups tool, letting you see all available backup records for a given account or resource type.

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Connect Vultr MCP to OpenAI Agents SDK

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

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Perplexity

Lifecycle Management

When you use `list_bare_metals`, your agent gets a full inventory of existing bare metal instances. It tells you which machines are running, halted, or stopped. Need to make changes? Your agent handles the entire process: it can `start_bare_metal` an instance that's off, `halt_bare_metal` one for maintenance, or even `reboot_bare_metal` if something's acting up.

Secure Credentials

Don't hardcode keys. Your agent manages security by using tools like `create_api_key`. This generates a new key and immediately lets you list existing ones with `list_api_keys`. It also gives you visibility into your account setup, letting you run `get_account` to confirm general Vultr account info.

Networking Setup

Setting up networking requires precision. Use the tool `setup_bgp` to configure Border Gateway Protocol for your account. This connects your agent directly to advanced network features. You can also get specific IP details, running checks like `get_bare_metal_ipv4` or `get_bare_metal_ipv6` against any bare metal instance.

Setup guide

Set up Vultr 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 Vultr tools at runtime.
3

Create your Agent

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

Run the agent

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

The agent auto-discovers all 19 tools available in the Vultr MCP Server. You simply pass the server definition to your Agent constructor, and it handles the rest.

The agent interacts with account configuration details, resource inventory, API keys, and specific network parameters like IPv4/IPv6 information. This is all managed through the MCP Server.

Yes. Since the agent uses async context managers and auto-discovers tools, it's built for production systems. You can reliably manage bare metal provisioning as part of your deployment flow.

Absolutely. The agent provides the `list_backups` tool, letting you see all available backup records for a given account or resource type.

This server touches core API keys and highly sensitive account configuration data, including network parameters (IPv4/v6) and BGP settings. Proper token management is required.

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