How to Use the Trengo MCP in OpenAI Agents SDK

Q: Can I list all contacts using Trengo and OpenAI Agents SDK?

Yep. The SDK supports calling listcontacts, which retrieves a full list of people associated with the account profile. This makes it easy for your agent to know who needs follow-up.

Q: How do I create a new webhook using Trengo and OpenAI Agents SDK?

You use the createwebhook tool within the agent's workflow. This lets you set up automated triggers for when certain events happen in your communication stream.

Q: What if I need to get current user profile info using Trengo and OpenAI Agents SDK?

You call getaccountprofile. This quickly pulls the necessary account details, which is helpful for scoping an agent's actions or verifying permissions.

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Connect Trengo MCP to OpenAI Agents SDK

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

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Manage conversations and tickets

Your agent can read all existing support threads using `list_tickets` or pull specific conversation history via `get_ticket`. It handles fetching team details with `list_team_members`, so it knows who's available to take over the chat. The system also lets you write new tickets with `create_ticket` and move status updates using `update_ticket`. This gives your agent full control over the ticket lifecycle.

Send messages and update data

The agent can initiate contact by sending a direct message via `send_message`, or it can get basic account info with `get_account_profile`. Need to track external changes? You'll use `create_webhook` to set up triggers on the Trengo MCP Server. It also lets you list contacts and channels. This means your agent doesn't just react; it knows who exists in the system, too.

Monitor webhooks and connections

You can check which triggers are active by calling `list_webhooks` or list all available communication channels using `list_channels`. This is crucial for setting up reliable external integrations. If you need to programmatically manage data, the agent supports listing existing webhooks and even retrieving a user's current profile via `get_account_profile`.

Setup guide

Set up Trengo 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 Trengo tools at runtime.
3

Create your Agent

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

Run the agent

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

The OpenAI Agents SDK auto-discovers all the available tools on the Trengo MCP Server. You just pass the endpoint, and your agent instantly knows it can handle tasks like `list_tickets` or `send_message`.

It handles several types of communication data. Specifically, the agent interacts with ticket status updates (`update_ticket`) and raw message content found via `list_messages`.

Yep. The SDK supports calling `list_contacts`, which retrieves a full list of people associated with the account profile. This makes it easy for your agent to know who needs follow-up.

You use the `create_webhook` tool within the agent's workflow. This lets you set up automated triggers for when certain events happen in your communication stream.

You call `get_account_profile`. This quickly pulls the necessary account details, which is helpful for scoping an agent's actions or verifying permissions.

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