Can I launch a high-performance H100 instance through my agent?

Yes. Use the `launch_instance` tool and specify the type (e.g. `gpu_1x_h100`) and region. Your agent will also allow you to attach registered SSH keys so the instance is securely accessible immediately upon boot.

How do I retrieve the Jupyter Lab access token for a running node?

Use the `get_instance` tool with your Instance ID. Your agent will fetch the complete telemetry, including the public IP and the Jupyter Lab access token if the environment is configured to provide it.

Can my agent check for GPU availability across different regions?

Absolutely. The `list_instance_types` tool queries the cloud boundary for hardware inventory. Your agent will report which GPU node types are currently available and in which physical regions they are hosted.

Lambda Labs (GPU Cloud) MCP Server for OpenAI Agents SDK 7 tools — connect in under 2 minutes

Name: Lambda Labs (GPU Cloud)
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 7 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Lambda Labs (GPU Cloud) through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Lambda Labs (GPU Cloud) Assistant",
            instructions=(
                "You help users interact with Lambda Labs (GPU Cloud). "
                "You have access to 7 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Lambda Labs (GPU Cloud)"
        )
        print(result.final_output)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Lambda Labs (GPU Cloud) MCP Server

Connect your Lambda Labs account to any AI agent and take full control of your AI infrastructure and high-performance GPU orchestration through natural conversation.

The OpenAI Agents SDK auto-discovers all 7 tools from Lambda Labs (GPU Cloud) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Lambda Labs (GPU Cloud), another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

Instance Orchestration — Launch state-of-the-art GPU virtual machines (e.g., H100, A100) and manage their entire lifecycle directly from your agent
ML Infrastructure Audit — List running instances and retrieve detailed hardware specifications, public IPv4 addresses, and Jupyter Lab access tokens securely
Inventory & Pricing — Discover available GPU node types and pricing matrices across different regions to optimize your AI training and inference budget
SSH Key Management — Enumerate globally managed public keys to ensure zero-trust infrastructure provisioning and secure access over port 22
Storage Mapping — Discover persistent shared NAS volumes living in the Lambda ecosystem that can be mounted simultaneously across multiple worker nodes
Resource Cleanup — Terminate and deallocate compute nodes instantly to stop billing and maintain a clean cloud footprint

The Lambda Labs (GPU Cloud) MCP Server exposes 7 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Lambda Labs (GPU Cloud) to OpenAI Agents SDK via MCP

Follow these steps to integrate the Lambda Labs (GPU Cloud) MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 7 tools from Lambda Labs (GPU Cloud)

Why Use OpenAI Agents SDK with the Lambda Labs (GPU Cloud) MCP Server

OpenAI Agents SDK provides unique advantages when paired with Lambda Labs (GPU Cloud) through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Lambda Labs (GPU Cloud) + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Lambda Labs (GPU Cloud) MCP Server delivers measurable value.

Automated workflows: build agents that query Lambda Labs (GPU Cloud), process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries Lambda Labs (GPU Cloud), another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Lambda Labs (GPU Cloud) tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Lambda Labs (GPU Cloud) to resolve tickets, look up records, and update statuses without human intervention

Lambda Labs (GPU Cloud) MCP Tools for OpenAI Agents SDK (7)

These 7 tools become available when you connect Lambda Labs (GPU Cloud) to OpenAI Agents SDK via MCP:

get_instance

Get exact details and SSH connection string for a specific instance

launch_instance

g., powerful H100 or A100 boxes). Injects explicit SSH keys into the runtime so it is securely accessible over port 22 immediately upon boot. Provision a new Lambda GPU virtual machine

list_filesystems

Map persistent shared NAS volumes living in the Lambda ecosystem

list_instance_types

Exposes exact catalog configurations of available GPU node types, identifying exactly which regions currently hold physical availability. Discover available Lambda GPU instance specifications and pricing

list_instances

List running GPU instances on Lambda Cloud

list_ssh_keys

Enumerate globally managed SSH public keys in Lambda

terminate_instances

Any ephemeral drives attached will be vaporized immediately without backup. Extremely destructive; stops billing instantly. Permanently terminate and destroy Lambda GPU instances

Example Prompts for Lambda Labs (GPU Cloud) in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Lambda Labs (GPU Cloud) immediately.

"List all my running GPU instances in Lambda Cloud"

"Launch a 1x H100 instance in us-east-1 with my 'default-key' SSH key"

"What are the available instance types and their current pricing?"

Troubleshooting Lambda Labs (GPU Cloud) MCP Server with OpenAI Agents SDK

Common issues when connecting Lambda Labs (GPU Cloud) to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Lambda Labs (GPU Cloud) + OpenAI Agents SDK FAQ

Common questions about integrating Lambda Labs (GPU Cloud) MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.