How to Use the Northflank (Developer Cloud & Orchestration) MCP in OpenAI Agents SDK

Q: Can my OpenAI Agents SDK handle build failures automatically?

Yes, the agent uses triggerbuild to start compilation and then monitors the deployment. If the build fails, the agent queries getservice to diagnose container issues.

Q: Does this setup support multiple projects?

Yes, the agent calls listprojects to discover all active project IDs. It then targets specific environments when running commands like listjobs or listservices.

Spin up environments and trigger builds directly from your OpenAI Agents SDK workflows with production-grade guardrails.

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Connect Northflank (Developer Cloud & Orchestration) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Northflank (Developer Cloud & Orchestration) 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 Northflank (Developer Cloud & Orchestration) with OpenAI Agents SDK

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Automate infrastructure teardown safely

The `delete_project` tool lets your agent tear down entire environments when testing runs finish using this MCP Server. Your OpenAI Agents SDK handles this with strict runtime guardrails, preventing the agent from executing catastrophic deletions without explicit human approval. You configure the SDK to intercept these high-impact commands. Before the agent triggers `delete_project` or `restart_service`, the system logs the intent to your tracing dashboard, giving you an audit trail of every container cycle.

Deploy code via OpenAI Agents SDK

The `trigger_build` tool instructs the builder to compile your latest commit. Your agent coordinates this build step, checks the output, and tracks the deployment status without you writing custom webhook handlers. When a build fails, the agent calls `list_services` to locate the broken container. It then reads the service configuration using `get_service` to identify misconfigured environment variables or scaling limits.

Audit environment variables and secrets

The `list_secrets` tool exposes active environment variables and database strings inside your VPC boundaries via the MCP connection. Your OpenAI agent inspects these values to verify that new builds have the correct credentials before routing live traffic. If a secret is missing, the agent halts the deployment pipeline. This integration prevents broken containers from booting, saving you from debugging failed startup probes in production.

Setup guide

Set up Northflank (Developer Cloud & Orchestration) 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 Northflank (Developer Cloud & Orchestration) tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK, then initialize the MCPServerStreamableHttp transport with your endpoint URL. Pass this server instance inside the mcp_servers list when instantiating your Agent class.

Yes, the agent uses `trigger_build` to start compilation and then monitors the deployment. If the build fails, the agent queries `get_service` to diagnose container issues.

You define custom verification functions in Python that intercept destructive actions sent through the MCP Server. The agent cannot execute `delete_project` unless your validation logic returns a positive confirmation.

Yes, the agent calls `list_projects` to discover all active project IDs. It then targets specific environments when running commands like `list_jobs` or `list_services`.

This MCP Server processes environment variables, database connection strings, and container metadata. Vinkius isolates this traffic inside ephemeral V8 sandboxes, meaning your API keys and configuration secrets are never stored or logged on our platform.

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