How to Use the NVIDIA AI MCP in OpenAI Agents SDK

Q: Can I swap models dynamically using NVIDIA AI with OpenAI Agents SDK?

Yes. You pass the model string to chatcompletion at runtime. The agent adapts to the model you specify, allowing for quick swaps between different model versions.

Q: Does NVIDIA AI provide embedding support for OpenAI Agents SDK?

It does. You use getembeddings to turn text into vectors. This is useful when you need to feed your agent context from documents or logs.

Connect your OpenAI Agents SDK to NVIDIA AI tools. Execute code, analyze sentiment, and run reasoning tasks in your production pipeline.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect NVIDIA AI MCP to OpenAI Agents SDK

Create your Vinkius account to connect NVIDIA 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.

GDPR Free for Subscribers

Setup NVIDIA AI with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Direct access to NVIDIA AI models

Your agent calls `chat_completion` directly through the MCP Server. It handles the message formatting so you get responses from Llama or Mistral without writing wrapper code. Everything stays within your existing agent flow. You pick the model, the server connects, and the agent processes the output.

Generate and validate code

Use `generate_code` to offload boilerplate or complex logic to the model. You get back raw code blocks ready for your agent to execute or store. It works exactly like a function call in your Python script. The agent identifies the task, hits the endpoint, and returns the result.

Automate data discovery

The `text_to_sql` tool bridges your natural language prompts and your database. Your agent translates intent into queries without manual intervention. This makes your agent an analyst. It reads your prompt, creates the SQL, and handles the retrieval logic for you.

Setup guide

Set up NVIDIA 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 NVIDIA AI tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives NVIDIA 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 NVIDIA 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="NVIDIA AI Agent",
            instructions="You have access to NVIDIA AI 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 NVIDIA. 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 NVIDIA AI 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 NVIDIA AI MCP in OpenAI Agents SDK

You manage authentication via the endpoint token provided by Vinkius. The server handles the handshake, keeping your API credentials out of your application code.

Yes. You pass the model string to `chat_completion` at runtime. The agent adapts to the model you specify, allowing for quick swaps between different model versions.

It does. You use `get_embeddings` to turn text into vectors. This is useful when you need to feed your agent context from documents or logs.

The server catches API exceptions and passes them back as standard tool errors. Your agent sees the failure immediately and can retry or log the issue.

Vinkius runs the server in an ephemeral sandbox. Your input text and prompt data are processed in memory and never persisted on our infrastructure.

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