How to Use the Convertio MCP in OpenAI Agents SDK

Convert files directly within your OpenAI Agents SDK production pipeline without leaving the code.

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Connect Convertio MCP to OpenAI Agents SDK

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

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Trigger file jobs via OpenAI Agents SDK

Your agent handles file tasks by calling `convert_file` directly. It ships the file URL to the API and waits for the job ID. You avoid manual uploads by letting the agent manage the entire lifecycle through `get_conversion_status`.

Manage conversion tasks in code

Clean up your workspace by using `delete_conversion_job` once the output is saved. It keeps your remote storage tidy. Check your remaining credits with `get_account_balance` before starting heavy batch jobs to ensure you don't hit limits.

Rapid format transformation

Use `quick_convert_to_jpg` for image processing or `quick_convert_to_pdf` for document tasks. It saves you from writing custom download logic. Query `list_common_formats` if you need to verify what extensions the service handles before you build the agent logic.

Setup guide

Set up Convertio 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 Convertio tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK and define an MCPServerStreamableHttp instance pointing to the server URL. Pass this object into your agent constructor to let the system discover tools automatically.

Yes. Set cacheToolsList to True when you define your server to keep performance high. This prevents the agent from re-fetching tool definitions every cycle.

Absolutely. Just call the tool and the agent will return your current balance as a simple integer. It makes tracking your usage during a long session easy.

Monitor the job status with the status tool. If a job fails, the agent can catch the response and log the specific error code to your trace dashboard.

Your files are processed on remote servers and deleted once you call the removal tool. We never store raw file content in your agent's persistent memory or trace logs.

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