How to Use the Avochato MCP in OpenAI Agents SDK

Use the OpenAI Agents SDK to push SMS and MMS data directly from your production code into Avochato.

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Connect Avochato MCP to OpenAI Agents SDK

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

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Automate contact management with OpenAI Agents SDK

Your agent can build your database by firing `create_contact` whenever a lead hits your funnel. It handles the record creation so your team stops manual entry. Keep tabs on your pipeline by calling `get_contact` or `list_contacts` to see who you are talking to. The SDK validates these actions before they hit the wire.

Execute messaging campaigns via MCP Server tools

Trigger `create_broadcast` to blast updates to your audience without leaving your Python script. It moves your marketing logic into your agent's control loop. Use `list_broadcasts` to check if your message queue is moving. You get real-time feedback on your campaign status inside the OpenAI dashboard.

Trace every SMS interaction in your agent system

Call `send_message` to reply to customers as soon as they reach out. Your agent manages the conversation flow through this MCP Server. Review your history with `list_messages` to maintain context. Every action shows up in your logs for audit.

Setup guide

Set up Avochato 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 Avochato tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Avochato 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="Avochato Agent",
            instructions="You have access to Avochato 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 Avochato MCP in OpenAI Agents SDK

You instantiate an MCPServerStreamableHttp object with your endpoint. The SDK discovers all ten tools automatically, so you can call them in your agent loop immediately.

Yes. The SDK guardrails catch failed requests before they break your logic. If a message fails, the agent knows why and can retry.

Vinkius runs this in an ephemeral V8 sandbox. Your credentials stay behind the endpoint token, and only your authorized agents access the data.

It does. Because the tools integrate directly into the agent lifecycle, every call appears in your standard tracing dashboard.

The server provides contact records, message history, and broadcast details. You only get access to the specific fields required to run your messaging automation.

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