How to Use the iZooto MCP in OpenAI Agents SDK

Q: How do I connect the iZooto MCP Server to OpenAI Agents SDK?

Install openai-agents first. Then, initialize MCPServerStreamableHttp with your server URL and pass it to the Agent constructor.

Q: How do I speed up tool discovery?

Set cacheToolsList=True in your connection parameters. This prevents the SDK from querying the MCP server for tool definitions on every single run.

Run safe, automated browser push campaigns directly from your OpenAI Agents SDK workflows to pull traffic back to your site.

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Connect iZooto MCP to OpenAI Agents SDK

Create your Vinkius account to connect iZooto 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 iZooto with OpenAI Agents SDK

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Segment audiences with OpenAI Agents SDK

Your OpenAI Agents SDK assistant can build laser-focused iZooto subscriber groups without manual database exports. By calling `create_segment` and inspecting existing groups with `list_segments`, the agent identifies high-value user cohorts right when traffic dips. This setup avoids broad-blast spamming across your browser channels. The OpenAI Agents SDK manages these specific iZooto tools with strict execution guardrails, ensuring your agent never targets the wrong group by mistake.

Execute safe push notifications on autopilot

Launching an iZooto campaign via OpenAI Agents SDK requires checking your current reach first. Your agent calls `get_subscriber_count` to verify the audience size before using `send_segment_push` to deliver the message. If the subscriber count is too low, the OpenAI Agents SDK hands off the task to a specialized optimization agent. This MCP server integration handles the API connections while the OpenAI dashboard traces every single call for debugging.

Trace push analytics inside your agent logs

Evaluating iZooto campaign success shouldn't require opening a separate marketing dashboard in your OpenAI Agents SDK workflows. Your agent uses `get_stats` to pull click-through rates and delivery metrics directly into your terminal. Using the `list_notifications` tool, the agent compares past performance to adjust future copy on the fly. This MCP integration lets you run closed-loop optimization cycles with zero manual intervention.

Setup guide

Set up iZooto 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 iZooto tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate iZooto 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="iZooto Agent",
            instructions="You have access to iZooto tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about iZooto MCP in OpenAI Agents SDK

Install `openai-agents` first. Then, initialize `MCPServerStreamableHttp` with your server URL and pass it to the `Agent` constructor.

Yes, you can control tool exposure through the SDK's agent configuration. This prevents the agent from calling high-impact tools like `send_push` without explicit approval.

The SDK relies on your agent's retry logic and standard HTTP error handling. If `send_segment_push` hits a rate limit, the agent detects the status code and pauses execution.

Set `cacheToolsList=True` in your connection parameters. This prevents the SDK from querying the MCP server for tool definitions on every single run.

Yes. The server only handles subscriber counts and segment definitions, passing them through an ephemeral V8 sandbox. No raw user data or personally identifiable information ever leaves your secure environment.

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