How to Use the Kling AI (Generative Video & Image) MCP in OpenAI Agents SDK

Q: How does the Kling AI (Generative Video & Image) integration work with the OpenAI Agents SDK's async features?

All generation tools like texttovideo are non-blocking. They return a task ID right away. You design your agent to use the corresponding get...task tool to check for completion, which fits perfectly with the async nature of the OpenAI SDK.

Build production-ready video agents with the safety and tracing of the OpenAI Agents SDK.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Kling AI (Generative Video & Image) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Kling AI (Generative Video & Image) 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.

GDPR Free for Subscribers

Setup Kling AI (Generative Video & Image) with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Generate Video Without Blocking Your Agent

Kick off a new video render with a single call to `text_to_video` or `image_to_video`. The tool immediately returns a task ID, freeing your agent to handle other work instead of getting stuck waiting for a long render to finish. This is how you build responsive, multi-skilled agents that don't freeze on long-running jobs. Your agent then uses `get_video_task` to poll for the result. With the OpenAI Agents SDK, you can use built-in guardrails to define polling intervals and timeouts. This prevents runaway API calls and gives you predictable behavior, which is critical before deploying your agent into a production environment.

Create Virtual Try-On Experiences

The `virtual_try_on` tool lets your agent map a garment onto a person in a photo. You provide the clothing image and the model's photo, and it composites them. Just like video generation, this tool returns a task ID so your agent isn't locked up. Your agent polls the `get_tryon_task` endpoint to get the final image URL. The OpenAI SDK's tracing dashboard shows every one of these attempts, so you can debug agent behavior and optimize how it waits for results. This fine-grained control is exactly what you need for building reliable e-commerce bots.

Build a Safer Kling AI MCP Server Agent

This MCP Server exposes ten distinct tools for generating and managing media. The OpenAI Agents SDK automatically discovers them, but its real strength is letting you create specialized agents that only have access to a subset of tools. For example, one agent might only be allowed to use `text_to_image` while another handles `lip_sync_video`. This separation of concerns is key for security and reliability. You can build handoffs where one agent generates a video and passes the task ID to a different 'poller' agent. It's a solid pattern for building complex, safe systems that work with the Kling AI toolset.

Setup guide

Set up Kling AI (Generative Video & Image) 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 Kling AI (Generative Video & Image) tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Kling AI (Generative Video & Image) 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="Kling AI (Generative Video & Image) Agent",
            instructions="You have access to Kling AI (Generative Video & Image) tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kling AI. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Kling AI (Generative Video & Image) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Kling AI (Generative Video & Image) MCP in OpenAI Agents SDK

All generation tools like `text_to_video` are non-blocking. They return a task ID right away. You design your agent to use the corresponding `get_..._task` tool to check for completion, which fits perfectly with the async nature of the OpenAI SDK.

Yes. The OpenAI Agents SDK is designed for this. You can create specialized agents and grant each one access to only specific tools from this MCP server, like allowing one to generate images but not videos.

Use the SDK's built-in guardrails. You can programmatically define rules for your agent, like limiting the polling frequency for `get_video_task` or setting a total timeout, to keep your API usage under control.

Use the OpenAI tracing dashboard. It provides a full, step-by-step log of every tool your agent calls, including all parameters and results. It’s the easiest way to debug your agent's interactions with Kling AI.

Your agent sends text prompts for generation and URLs for source images or videos. All traffic is encrypted between your agent and the Vinkius-managed server. The OpenAI SDK also adds a layer of control, letting you validate actions before they're ever executed.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript