How to Use the DeepAI MCP in OpenAI Agents SDK

Connect DeepAI to your OpenAI Agents SDK setup for production-grade image generation and editing pipelines.

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Connect DeepAI MCP to OpenAI Agents SDK

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

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Text-to-Image with Guardrails via OpenAI Agents SDK

The DeepAI MCP server provides image creation and editing endpoints directly to your Python agents. You call `generate_image` with a text prompt, and the agent handles the execution. Because you are using the OpenAI Agents SDK, every image request passes through your defined safety constraints before hitting the API. If a user asks for inappropriate content, your tracing dashboard catches the rejected prompt before the network call happens.

Handoff Specialized Image Tasks

Modifying existing visuals requires precise tool execution. Your router agent can hand off tasks to a dedicated design agent equipped with MCP tools like `remove_background` and `edit_image`. This multi-agent setup keeps your code clean. One agent handles text processing, while the second agent applies the DeepAI modifications and returns the final asset URL back up the chain.

Upscale and Colorize Legacy Assets

Processing historic or low-quality photos is straightforward with the `colorize_image` and `super_resolution` tools. The agent reads a black-and-white source file and returns a sharp, colorized output. Performance matters in production environments. Setting cacheToolsList=True in your MCPServerStreamableHttp configuration prevents the agent from re-fetching the tool definitions on every single upscale request.

Setup guide

Set up DeepAI 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 DeepAI tools at runtime.
3

Create your Agent

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

Run the agent

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

Run pip install openai-agents in your environment. Then initialize MCPServerStreamableHttp with your Vinkius endpoint URL and pass it to the mcp_servers array.

Yes, every execution of a DeepAI tool appears in your OpenAI dashboard. You see the exact prompt sent and the resulting image URL.

No, the agent auto-discovers them. Once connected, tools like background removal and upscaling populate automatically.

The agent catches the HTTP error and triggers your configured fallback logic. You define the retry parameters directly in your Python code.

The server processes raw image files and text prompts. Vinkius runs this MCP integration inside an ephemeral V8 Isolate sandbox, meaning your visual assets disappear from memory the moment the request finishes.

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