How to Use the CatAAS MCP in OpenAI Agents SDK

Inject cat memes directly into your OpenAI Agents SDK production workflows with this MCP Server.

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Connect CatAAS MCP to OpenAI Agents SDK

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

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Perplexity

Dynamic image generation for OpenAI Agents SDK

Your agent uses `get_cat_with_text` to overlay custom captions on random cat images. This happens automatically within your defined safety guardrails. Since you use `cacheToolsList=True`, the agent keeps these functions ready for immediate execution during production runs.

Filter and select cats via agent logic

The agent calls `list_tags` to inventory available categories before invoking `get_cat_by_tag` to fetch a specific match. You get exact, traced results in your OpenAI dashboard. This ensures your agent isn't guessing outcomes. It follows the explicit schema provided by the MCP Server to maintain system stability.

Animated content injection

Call `get_random_gif_cat` to pull high-quality GIFs into your agent's response payload. It adds visual flair to automated communications. Your agent handles the binary data directly. The OpenAI Agents SDK manages the transfer without extra configuration overhead.

Setup guide

Set up CatAAS 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 CatAAS tools at runtime.
3

Create your Agent

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

Run the agent

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

Use the MCPServerStreamableHttp class to point your agent at the Vinkius endpoint. Pass the result into the mcp_servers list within your agent constructor.

Yes, set cacheToolsList to True when initializing the server connection. This prevents unnecessary network round-trips for tool discovery.

The server manages the load independently of your agent logic. Each request is scoped to the specific execution context of your worker.

The server fetches metadata on demand from the API provider. No persistent storage is maintained on your agent infrastructure.

We only touch public image URLs and text strings. Your agent's internal state and private data never leave your controlled runtime environment.

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