How to Use the Convertlab MCP in AutoGen

Q: How do I register Convertlab tools with AutoGen?

Install autogen-extmcp and use mcpservertools with your Vinkius HTTP URL. Pass the resulting tools list directly to your AssistantAgent constructor.

Q: Can AutoGen agents debate Convertlab campaign strategies?

Yes. One agent calls listcampaigns to analyze past performance, while another queries listtouchpoints to suggest improvements, debating the results in a shared chat.

Let AutoGen agents debate and coordinate marketing actions using live Convertlab customer data.

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Connect Convertlab MCP to AutoGen

Create your Vinkius account to connect Convertlab 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 Convertlab with AutoGen

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Run consensus-driven marketing with AutoGen

Execute `create_customer` and `list_touchpoints` inside collaborative agent conversations. A performance agent analyzes touchpoints, while a compliance agent reviews the customer profile before writing to your database. This MCP Server lets your agents debate the best course of action. They negotiate the parameters of each marketing operation before executing the tool call.

Coordinate campaign reviews across multiple agents

Query campaign data using `get_campaign` and `list_events` to fuel agent discussions. One agent drafts the event follow-up, another checks the campaign goals, and a third runs the actual tool to verify details. AutoGen handles the schema conversion automatically using the McpToolAdapter. You don't have to manually write JSON schemas for your agents to understand the marketing data.

Automate segment verification with the MCP Server

Retrieve customer segments using `list_member_groups` and `list_customers` during multi-agent planning. Your agents cross-reference these lists to ensure target audiences are correctly defined before launching campaigns. The framework supports both stdio and streamable HTTP transports. This flexibility allows your agents to query customer records reliably during long-running planning sessions.

Setup guide

Set up Convertlab 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 Convertlab 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="Convertlab_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Install autogen-ext[mcp] and use mcp_server_tools with your Vinkius HTTP URL. Pass the resulting tools list directly to your AssistantAgent constructor.

Yes. One agent calls list_campaigns to analyze past performance, while another queries list_touchpoints to suggest improvements, debating the results in a shared chat.

The McpToolAdapter automatically maps the server's tool definitions into the format AutoGen expects. This removes the need for manual schema mapping when setting up your agents.

Yes. You can connect using Streamable HTTP transport parameters. This allows your multi-agent system to interact with the marketing server over a stable web connection.

Your event lists and customer details are processed within a zero-trust, ephemeral V8 container. Vinkius manages the secure connection, ensuring no raw credentials leak during agent debates.

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