How to Use the Moloco MCP in AutoGen

Debate your ad strategy with AutoGen agents that use Moloco data to reach consensus.

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Connect Moloco MCP to AutoGen

Create your Vinkius account to connect Moloco 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 Moloco with AutoGen

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Perplexity

Consensus-Driven Ad Management

Deploy multiple agents to debate campaign performance using data from `list_conversions`. One agent checks for risks while another looks for growth opportunities. This ensures your decisions are vetted by different perspectives. You get a balanced strategy before any changes are made to your account.

Automated Campaign Adjustments

Use `update_campaign_status` once your agents reach a consensus. The decision-making process is transparent and based entirely on the data returned by your tools. This removes the subjectivity from your ad-ops. You get a verifiable trail of how and why a campaign status was changed.

Multi-Agent Tool Debates

Have your agents challenge each other using reports from `get_analytics_report`. They can compare performance across different creative groups to find the best angle. This forces a rigorous review of your data. You end up with a strategy that has been stress-tested by your own AI agents.

Setup guide

Set up Moloco 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 Moloco 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="Moloco_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You use the MCP extension to connect the server, then pass the tools to your AssistantAgent. The adapter handles the schema so your agents can talk to the API immediately.

Yes, they can list campaigns, check analytics, and update statuses. By discussing the data, they ensure that changes are grounded in performance metrics.

The server uses a zero-trust architecture and ephemeral sessions. Your credentials and ad data are never stored, only processed in-memory during the agent conversation.

Your agent's conversation logs will show the tool calls and their outputs. This lets you review the exact data used by your agents to make their decisions.

Conversion events are fetched directly from the API and delivered straight to your agent. Since the server is ephemeral, your sensitive event data is never written to disk or shared.

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