How to Use the Vectorizer AI MCP in OpenAI Agents SDK

Q: If I need to clean up old files, how do I use Vectorizer AI with OpenAI Agents SDK?

You call deleteimage when you want to remove a stored image. This tool works based on retention policies, so it’s reliable for cleaning up assets that have passed their mandated storage time.

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Connect Vectorizer AI MCP to OpenAI Agents SDK

Create your Vinkius account to connect Vectorizer AI 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 Vectorizer AI with OpenAI Agents SDK

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Vectorize images using the MCP Server

The `vectorize_image` tool takes bitmap files—like JPGs or PNGs—and converts them into scalable vector formats such as SVG, EPS, PDF, and DXF. You get high-quality, tracing results ready for professional design use. It's perfect when you need to take a scanned sketch or a raster logo and turn it into clean, mathematically defined geometry that won't lose quality when scaled up.

Managing assets with the OpenAI Agents SDK

Need to pull out specific files? The `download_image` tool lets you download a finished product or an alternative format of your vector asset. This ensures you always have the right file type for whatever downstream process you're running. You can also use `delete_image` if you need to remove a stored image based on policy retention dates, keeping your data clean and compliant.

Checking system status via MCP Server

The `get_account_status` tool lets your agent check the subscription details and remaining credits for the Vectorizer AI service. This is crucial for production agents because they need to know if they can afford the next job. It gives you a clear picture of resource availability, so your agent doesn't fail halfway through a complex task just because the credit limit was hit.

Setup guide

Set up Vectorizer AI 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 Vectorizer AI tools at runtime.
3

Create your Agent

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

Run the agent

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

The agents treat the MCP Server like any other specialized tool. When your agent needs a vector, it simply calls the `vectorize_image` function. The system handles passing the bitmap data to the server and receiving the finished vector file back.

Yeah, you can pass a request that asks for several formats in one go. The server supports delivering SVG, EPS, PDF, and DXF outputs from the same input image. Just specify what you need when calling `vectorize_image`.

Because you're building a deployed product, make sure your agent calls check the account status first. Using `get_account_status` ensures that the subsequent vectorization job doesn't fail due to unexpected billing issues.

You call `delete_image` when you want to remove a stored image. This tool works based on retention policies, so it’s reliable for cleaning up assets that have passed their mandated storage time.

This server handles the raw JPG and PNG bitmap image tokens. The agent interacts with these specific types when calling `vectorize_image` or `download_image`, so you know exactly what data is being processed.

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