How to Use the AdRoll MCP in AutoGen

Q: How do I configure the AdRoll MCP Server for AutoGen?

Install autogen-extmcp. You initialize mcpservertools with a StreamableHttpServerParams object pointing to Vinkius, then pass the resulting list to your AssistantAgent.

Q: Can AutoGen agents trigger AdRoll performance reports?

Yes. The McpToolAdapter handles the schema conversion automatically. Your data analysis agent can call the reporting tool and drop the statistics straight into the group chat.

Build AutoGen agent debates where competing AI models analyze AdRoll performance metrics and negotiate e-commerce budgets.

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Connect AdRoll MCP to AutoGen

Create your Vinkius account to connect AdRoll 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 AdRoll with AutoGen

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Perplexity

Multi-Agent MCP Server Workflows

`get_performance_report` delivers raw return-on-ad-spend statistics to your AutoGen conversation thread. A financial agent reviews the numbers to flag inefficient spend while a growth agent argues for scaling the budget. They debate the findings until they reach a consensus. You build a system that refuses to make unilateral marketing decisions without cross-checking the data from multiple distinct perspectives.

Audit Ad Creatives Objectively

`list_ads` dumps your current active inventory into the chat context. One agent analyzes the text and format variations, while another checks the historical click-through rates. `get_campaign_details` adds the targeting parameters to the discussion. The agents cross-reference the visual assets against the audience restrictions to spot mismatched messaging.

Map Advertiser Account Structures

`list_advertisables` retrieves the top-level account hierarchy for your agency or brand. The framework parses this list so your routing agent knows exactly which sub-accounts exist. `list_campaigns` then fires for each specific ID. Your agents divide the workload, assigning different bots to monitor different product lines simultaneously.

Setup guide

Set up AdRoll 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 AdRoll 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="AdRoll_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent AdRoll 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 AdRoll. 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 AdRoll MCP in AutoGen

Install `autogen-ext[mcp]`. You initialize `mcp_server_tools` with a `StreamableHttpServerParams` object pointing to Vinkius, then pass the resulting list to your `AssistantAgent`.

Yes. The `McpToolAdapter` handles the schema conversion automatically. Your data analysis agent can call the reporting tool and drop the statistics straight into the group chat.

Marketing requires balancing risk and growth. You assign one agent to act as a strict budget controller and another as a creative strategist, letting them debate the API data before suggesting changes.

No. You typically give the tool execution capabilities to a single designated agent. The other models simply read the output and provide their specialized analysis.

Your creative assets, budget caps, and performance metrics process through a zero-trust V8 Isolate Sandbox. The Vinkius infrastructure spins up ephemerally for the session and wipes all memory of your e-commerce operations immediately after execution.

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