How to Use the Bunny.net MCP in OpenAI Agents SDK

Q: How do I handle storage zone creation using Bunny.net in OpenAI Agents SDK?

Your Python script initializes the agent with the addstoragezone tool exposed. The agent can bootstrap NY-based storage volumes and hand off the credentials to specialized file-handling agents.

Q: Does this MCP Server support dynamic CDN lookups?

Yes, your agent can execute live calls like listpullzones instantly. Setting cacheToolsList=True improves execution speed by preventing the SDK from querying the server for tool definitions on every turn.

Q: Where do my Bunny.net FTP passwords go during file listings?

The API keys and FTP passwords needed for listfiles remain inside the Vinkius secure environment. The OpenAI Agents SDK only receives the structured output containing byte lengths and hashes, keeping raw credentials out of the prompt history.

Spin up Bunny.net CDN zones and purge edge caches safely using this MCP Server inside your OpenAI Agents SDK production deployment.

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Connect Bunny.net MCP to OpenAI Agents SDK

Create your Vinkius account to connect Bunny.net 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 Bunny.net with OpenAI Agents SDK

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Safe Edge Provisioning with OpenAI Agents SDK

Production deployments need safety rails when spin-ups occur. Your OpenAI Agents SDK workflow can now safely initiate CDN zones using `add_pull_zone` without manual API scripting. The SDK checks agent actions against your strict guardrails before any global routing changes go live. If a zone requires teardown, the agent calls `delete_pull_zone` to instantly drop old proxy connections. This keeps your runtime secure because the SDK traces every single step on the OpenAI dashboard, making sure no rogue CDN targets slip through.

Automated Cache Purging via Edge Tools

When your origin content changes, you need immediate cache invalidation. This MCP Server lets your agent trigger `purge_pull_zone` right when a deployment pipeline finishes. It prevents stale assets from lingering on the global Anycast network. The agent handles the origin re-fetch signal autonomously, checking edge rules with `get_pull_zone` first to confirm SSL and bandwidth limits. Because the OpenAI Agents SDK caches the tool list, this check happens with zero latency overhead.

Secure Storage Volume Bootstrapping

Provisioning isolated storage shouldn't expose your master credentials to autonomous loops. Your agents can spin up empty volumes using `add_storage_zone` and immediately grab FTP access keys via `get_storage_zone`. If an agent tries to touch unauthorized directories, your SDK handoffs pass the task to a restricted sub-agent. This keeps your Bunny.net storage credentials locked down while letting the system run file operations via `list_files` automatically.

Setup guide

Set up Bunny.net 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 Bunny.net tools at runtime.
3

Create your Agent

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

Run the agent

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

You configure the MCP Server as a streamable HTTP target within your Python code. Pass the endpoint to your agent initialization block, and the SDK auto-discovers all ten edge routing tools.

Yes, you can set up explicit guardrails on the SDK side to restrict the `purge_pull_zone` tool. This ensures your agent only clears caches under validated pipeline triggers.

Your Python script initializes the agent with the `add_storage_zone` tool exposed. The agent can bootstrap NY-based storage volumes and hand off the credentials to specialized file-handling agents.

Yes, your agent can execute live calls like `list_pull_zones` instantly. Setting `cacheToolsList=True` improves execution speed by preventing the SDK from querying the server for tool definitions on every turn.

The API keys and FTP passwords needed for `list_files` remain inside the Vinkius secure environment. The OpenAI Agents SDK only receives the structured output containing byte lengths and hashes, keeping raw credentials out of the prompt history.

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