Heroku (PaaS) MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Heroku (PaaS) through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="Heroku (PaaS) Assistant",
instructions=(
"You help users interact with Heroku (PaaS). "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Heroku (PaaS)"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Heroku (PaaS) MCP Server
Connect your Heroku account to any AI agent and take full control of your cloud-native application management and dyno orchestration through natural conversation.
The OpenAI Agents SDK auto-discovers all 10 tools from Heroku (PaaS) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Heroku (PaaS), another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- App Management — List all hosted applications, create new deployment boundaries, and fetch intricate runtime constraints and framework details directly from your agent
- Dyno Orchestration — List individual containerized dynos, track their status (up, crashed, idle), and selectively reboot specific instances or entire clusters
- Environment & Config — Audit decrypted application environment variables (Config Vars) and retrieve third-party platform add-ons like Postgres or Redis
- Operational Control — Rapidly toggle maintenance mode to block inbound requests during migrations and perform hard reboots on stalled application clusters
- Infrastructure Audit — Identify underlying executing stacks (e.g. heroku-24), regional datacenter placements (US/EU), and total slug size in memory
The Heroku (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 Heroku (PaaS) to OpenAI Agents SDK via MCP
Follow these steps to integrate the Heroku (PaaS) MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from Heroku (PaaS)
Why Use OpenAI Agents SDK with the Heroku (PaaS) MCP Server
OpenAI Agents SDK provides unique advantages when paired with Heroku (PaaS) through the Model Context Protocol.
Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Heroku (PaaS) + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Heroku (PaaS) MCP Server delivers measurable value.
Automated workflows: build agents that query Heroku (PaaS), process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Heroku (PaaS), another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Heroku (PaaS) tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Heroku (PaaS) to resolve tickets, look up records, and update statuses without human intervention
Heroku (PaaS) MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Heroku (PaaS) to OpenAI Agents SDK via MCP:
create_app
Provision a fresh structural App container on Heroku
delete_app
Traffic routing instantly yields persistent 404/no web-dynos responses. Highly destructive. Permanently wipe an active App from Heroku servers
get_app_info
g. heroku-22, heroku-24). Confirms exact application routing URL mapping, total slug (code) size in memory, and regional datacenter placements (US or EU) verifying global latency strategies. Fetch intricate runtime constraints and framework details of an App
list_addons
Retrieve third-party Platform Add-ons mapping to an App
list_apps
Use this to discover App IDs, web URL designations, and git repository targets required to execute operational commands downstream. List all standard applications actively hosted on Heroku PaaS
list_config_vars
Retrieves highly confidential database tokens `DATABASE_URL`, SendGrid passwords, or OAuth keys. Dump decrypted Application Environment Variables
list_dynos
1, worker.1). Tracks exactly whether the dyno is "up", "crashed", "idle", or "starting" based on the internal slug runner engine's telemetry. List discrete containerized Dynos executing inside an App
restart_all_dynos
Often resolves ephemeral memory-leaks in Node.js or Ruby runtimes stalling standard request processing. Hard reboot all containers tied to an entire Application
restart_specific_dyno
Exceedingly useful for unsticking hung asynchronous queue workers without impacting active web traffic on the primary frontend replicas. Selectively reboot one isolated Dyno instance (e.g. worker.2)
toggle_maintenance_mode
Crucial for orchestrating complex sequential database migrations without encountering corrupted states from active sessions. Rapidly switch an Application's Maintenance Mode switch
Example Prompts for Heroku (PaaS) in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Heroku (PaaS) immediately.
"List all my Heroku apps"
"Restart all dynos for 'production-api'"
"What's the current maintenance mode status for the 'staging-web' app?"
Troubleshooting Heroku (PaaS) MCP Server with OpenAI Agents SDK
Common issues when connecting Heroku (PaaS) to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Heroku (PaaS) + OpenAI Agents SDK FAQ
Common questions about integrating Heroku (PaaS) MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Heroku (PaaS) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Heroku (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.