How to Use the Convertlab MCP in OpenAI Agents SDK

Run guarded, production-ready marketing workflows in Convertlab using the OpenAI Agents SDK.

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Connect Convertlab MCP to OpenAI Agents SDK

Create your Vinkius account to connect Convertlab to OpenAI Agents SDK 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 OpenAI Agents SDK

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Query customer data with OpenAI Agents SDK

`list_customers` lets your OpenAI agent pull real-time profiles from your Convertlab DM Hub directly into your run context. The agent parses customer records and updates profiles with `create_customer` when new contact details arrive. You get strict runtime tracing through the OpenAI dashboard to watch exactly how your agent queries `get_customer`. If an agent tries to modify a profile, the SDK's built-in guardrails validate the payload before Convertlab executes the change.

Analyze active marketing campaigns

`list_campaigns` exposes your current marketing initiatives to specialized OpenAI agents. The agent uses `get_campaign` to inspect performance metrics and decide which segments need follow-up actions. Hand off tasks between dedicated agents when campaign data requires different actions. A triage agent pulls the campaign list, then routes the data to a specialist agent that schedules touchpoints based on what it finds.

Track touchpoints and segments via MCP Server

`list_touchpoints` gives your OpenAI agent visibility into user interactions across your marketing channels. The agent correlates these interactions with segments retrieved from `list_member_groups` to map customer journeys. This MCP Server allows your agent to cross-reference active marketing events via `list_events`. Your production Python code handles the execution while OpenAI handles the reasoning, keeping your marketing stack synchronized.

Setup guide

Set up Convertlab MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Convertlab tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Convertlab tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Convertlab tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Convertlab Agent",
            instructions="You have access to Convertlab tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 OpenAI Agents SDK

Install the SDK, then initialize the MCPServerStreamableHttp class pointing to your Vinkius endpoint. Pass this server instance in the mcp_servers list when constructing your OpenAI Agent. The agent automatically discovers tools like `list_customers` and `get_campaign` without manual JSON schema definition.

Yes. You control tool exposure by defining specific system instructions or restricting the server list in your Python code. This prevents the OpenAI agent from calling structural tools like `create_customer` while still allowing read-only access to `list_campaigns`.

Set the cacheToolsList parameter to True in your MCPServerStreamableHttpParams config. This stops the agent from repeatedly querying the Vinkius MCP Server for the tool schema, reducing latency on frequent calls to `list_touchpoints`.

Yes. The connection runs inside an async context manager in your Python service. Your OpenAI agent handles high-throughput marketing events by querying `list_events` asynchronously without blocking your main application loop.

Vinkius runs this integration in an ephemeral V8 sandbox, ensuring your customer profiles and marketing event logs are never stored on the hosting platform. Transmission of sensitive data from `get_customer` to OpenAI is encrypted in transit and subject to your enterprise OpenAI data opt-out policies.

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