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Porter PaaS MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Porter PaaS through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Porter PaaS Assistant",
            instructions=(
                "You help users interact with Porter PaaS. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Porter PaaS"
        )
        print(result.final_output)

asyncio.run(main())
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About Porter PaaS MCP Server

Connect your Porter account to any AI agent and take full programmatic control over your Kubernetes infrastructure natively.

The OpenAI Agents SDK auto-discovers all 10 tools from Porter PaaS through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Porter PaaS, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

  • Projects & Clusters — List high-level organizational bounds, EKS/GKE clusters, and deployment zones
  • Applications & Environments — Map staging/production namespaces, check active web services, and resolve container requirements
  • Operations — Restart app pods gracefully or forcefully deploy specific image tags when resolving CI/CD breaks
  • Helm Inspections — Check low-level Helm charts behind active components (like Postgres or Redis)

The Porter PaaS MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Porter PaaS to OpenAI Agents SDK via MCP

Follow these steps to integrate the Porter PaaS MCP Server with OpenAI Agents SDK.

01

Install the SDK

Run pip install openai-agents in your Python environment

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

03

Run the script

Save the code above and run it: python agent.py

04

Explore tools

The agent will automatically discover 10 tools from Porter PaaS

Why Use OpenAI Agents SDK with the Porter PaaS MCP Server

OpenAI Agents SDK provides unique advantages when paired with Porter PaaS through the Model Context Protocol.

01

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

02

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

03

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

04

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Porter PaaS + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Porter PaaS MCP Server delivers measurable value.

01

Automated workflows: build agents that query Porter PaaS, process the data, and trigger follow-up actions autonomously

02

Multi-agent orchestration: create specialist agents. one queries Porter PaaS, another analyzes results, a third generates reports

03

Data enrichment pipelines: stream data through Porter PaaS tools and transform it with OpenAI models in a single async loop

04

Customer support bots: agents query Porter PaaS to resolve tickets, look up records, and update statuses without human intervention

Porter PaaS MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect Porter PaaS to OpenAI Agents SDK via MCP:

01

deploy_app_tag

Assigns a raw docker registry digest/tag directly causing Kubernetes to perform an absolute image pull orchestrating a fresh deployment state spanning replica boundaries. Forcefully mutate the executed Docker image running internally

02

get_app

Includes explicit CPU metrics requested, RAM limits mapped locally to the JVM/Node instances, and internal registry image hashes resolving at runtime. Analyze architectural bindings orchestrating a specific App

03

get_cluster

Inspect deep cloud credentials generating a specific K8s Cluster

04

get_project

Perform structural extraction of metadata linked to a Porter Project

05

list_apps

Discovers precisely which App routing identities expose `porter.run` subdomains or linked target custom apex mappings. Inventory deployed discrete Applications mapping to a Cluster

06

list_clusters

Exposes crucial execution zones hosting absolute memory nodes. List underlying target cloud Kubernetes definitions bounds to Porter

07

list_environments

Extract logic isolation environments overlapping the Cluster

08

list_helm_releases

Vital for verifying if dependent third-party apps (e.g. Postgres databases or Metabase) deployed aside the primary stack succeeded during installation phases. List underlying operational Helm configurations inside a namespace

09

list_projects

Fetches indispensable integer `projectId` arrays coordinating everything strictly downstream inside AWS/GCP clusters. Identify base Porter PaaS organizational scopes

10

restart_app

Mandatory during severe connection leakage scenarios impacting native processes without modifying the fundamental code layer deployment tag. Instruct the Kubernetes API to bounce the App deployment replicas

Example Prompts for Porter PaaS in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Porter PaaS immediately.

01

"List all applications currently running in cluster ID 5 on the Production environment."

02

"The queue worker is completely hung. Please perform a forceful restart of the `async-worker` app."

03

"We just built a hotfix on main. Deploy the image tag `d83a1b1` strictly onto `portal-frontend`."

Troubleshooting Porter PaaS MCP Server with OpenAI Agents SDK

Common issues when connecting Porter PaaS to OpenAI Agents SDK through the Vinkius, and how to resolve them.

01

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents
02

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Porter PaaS + OpenAI Agents SDK FAQ

Common questions about integrating Porter PaaS MCP Server with OpenAI Agents SDK.

01

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.
02

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.
03

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.

Connect Porter PaaS to OpenAI Agents SDK

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.