How to Use the Klaviyo (Marketing Automation) MCP in AutoGen

Q: How do I register the Klaviyo (Marketing Automation) tools with an AutoGen agent?

Use mcpservertools with your Vinkius server URL to fetch the tools. Pass this list to your AssistantAgent constructor, and the McpToolAdapter will handle the schema setup automatically.

Q: Can AutoGen agents collaborate to update lists in Klaviyo (Marketing Automation)?

Yes. You can have one agent analyze segments using listaudiencesegments and another call addprofilestolist to update lists based on the first agent's analysis.

Build AutoGen multi-agent teams that debate and coordinate Klaviyo marketing campaigns and list management.

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Connect Klaviyo (Marketing Automation) MCP to AutoGen

Create your Vinkius account to connect Klaviyo (Marketing Automation) 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 Klaviyo (Marketing Automation) with AutoGen

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Perplexity

Multi-agent debate over Klaviyo campaign performance

Set up an AutoGen team where one agent pulls active broadcasts using `list_email_campaigns` and another reviews details using `get_campaign_details` using our MCP tools. They can argue about which copy performed best before making changes. A third agent can look at `list_automation_flows` to see if the campaigns align with active flows. This collaborative review ensures your broadcast strategy matches your automated journeys.

Safe profile coordination via AutoGen consensus

Before adding users to a list, your agents can coordinate over the MCP connection. A targeting agent uses `list_profiles` to find candidates, while a compliance agent checks their properties using `get_profile` to ensure they opted in. Only when both agents agree does the executor agent call `add_profiles_to_list`. This consensus-driven approach prevents accidental spamming and keeps your lists clean.

Multi-agent validation for new Klaviyo profiles

When importing new leads, one agent can draft the profile data while another validates the format. They use `create_profile` only after confirming the email and names are structured correctly. The agents can then check `list_lists` to find the correct onboarding group and place the new profile there, handling the entire setup autonomously through structured conversation.

Setup guide

Set up Klaviyo (Marketing Automation) 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 Klaviyo (Marketing Automation) 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="Klaviyo (Marketing Automation)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Klaviyo (Marketing Automation) 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="Klaviyo (Marketing Automation)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Klaviyo (Marketing Automation) 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 Klaviyo. 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.

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Common questions about Klaviyo (Marketing Automation) MCP in AutoGen

Use mcp_server_tools with your Vinkius server URL to fetch the tools. Pass this list to your AssistantAgent constructor, and the McpToolAdapter will handle the schema setup automatically.

Yes. You can have one agent analyze segments using list_audience_segments and another call add_profiles_to_list to update lists based on the first agent's analysis.

By requiring a debate. A safety agent can review profiles fetched with get_profile and veto any create_profile calls if the data doesn't meet your formatting standards.

It uses Streamable HTTP transport via Vinkius, which handles the connection and authentication securely, converting the tools into schemas the agents understand.

All operations, including retrieving predictive analytics via get_profile, run in a zero-trust, isolated sandbox. Your customer purchase history and CLV metrics are never cached or exposed to external networks.

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