How to Use the Heroku (PaaS) MCP in AutoGen

Use AutoGen agents to debate and manage your Heroku (PaaS) environment with multi-agent consensus.

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Connect Heroku (PaaS) MCP to AutoGen

Create your Vinkius account to connect Heroku (PaaS) to AutoGen 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 Heroku (PaaS) with AutoGen

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Perplexity

Multi-agent Heroku (PaaS) control

Assign one agent to monitor logs and another to execute `restart_specific_dyno`. They debate the necessity of a reboot before taking action. This prevents hasty decisions. The agents verify the state via `list_dynos` before confirming that a restart is the right move for your production environment.

Debate infrastructure changes

Let your team of agents discuss whether to `toggle_maintenance_mode` during a migration. They compare the risks and benefits based on the app info provided. You get a reasoned decision backed by multiple perspectives. It ensures that critical infrastructure changes undergo scrutiny before execution.

Automated Heroku (PaaS) auditing

Have one agent audit your `list_config_vars` while another flags missing entries. They work together to ensure your production environment stays secure. The agents cross-reference your required settings against the live data. It catches configuration drift before it causes an outage.

Setup guide

Set up Heroku (PaaS) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Heroku (PaaS) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Heroku (PaaS)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Heroku (PaaS) data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Heroku (PaaS)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Heroku (PaaS) data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about Heroku (PaaS) MCP in AutoGen

The MCP adapter converts the server tools into functions the agents call during their conversation. They use these tools to gather information and perform actions.

Yes, agents can list all your applications and drill down into specific ones. They manage the scope of their conversation to focus on the right app.

You can set up your agents with limited permissions or include a human-in-the-loop step. This allows them to propose actions while you retain final approval.

You just need the MCP server endpoint and the adapter installed. The agents handle the rest by including the tool definitions in their system prompts.

The server uses your authenticated token to connect. The agents don't see your raw credentials; they only interact with the tools provided by the server.

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