How to Use the AdButler MCP in AutoGen

Q: Can AutoGen optimize my AdButler zones?

Your agents can compare listzones and getstats to find underperforming areas. They then present their findings for you to approve.

Let your AutoGen agents debate campaign strategies using live metrics pulled from AdButler.

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Connect AdButler MCP to AutoGen

Create your Vinkius account to connect AdButler 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 AdButler with AutoGen

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Perplexity

AutoGen agents debate AdButler tasks

One agent calls `check_adbutler_status` while another reviews `list_zones`. They discuss the findings to decide if your ad delivery is healthy. This approach avoids single-point errors. You get a consensus-based view on your ad performance from agents that challenge each other.

Negotiate ad placements

Your agents use `list_placements` and `list_banners` to identify bottlenecks. They negotiate the best strategy to move inventory before suggesting a change. It puts your strategy through a stress test. You see the deliberation process as the agents weigh different options against your current data.

Coordinate via AdButler tools

The McpToolAdapter automatically converts your server tools for the agents to use. They execute these calls as part of their conversation flow. Everything happens in real-time. You watch the agents talk through the data and pick the right tool for the job.

Setup guide

Set up AdButler 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 AdButler 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="AdButler_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent AdButler 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="AdButler_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AdButler. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about AdButler MCP in AutoGen

Pass the server tools into your AssistantAgent constructor. The adapter handles the schema, allowing your agents to invoke tools during their debate.

Your agents can compare `list_zones` and `get_stats` to find underperforming areas. They then present their findings for you to approve.

They might, but that is the point. You define the agents' roles so they challenge each other until they reach a decision that fits your goals.

It does. You can share the tool list across any number of agents in your conversation group, letting everyone access the same data.

Your advertiser names, campaign performance, and zone settings are handled in a zero-trust environment. We isolate all execution to prevent data leaks.

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