Lambda Labs (GPU Cloud) MCP Server for Cursor 7 tools — connect in under 2 minutes
Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.
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The modern way to manage MCP Servers — no config files, no terminal commands. Install Lambda Labs (GPU Cloud) and 2,500+ MCP Servers from a single visual interface.
{
"mcpServers": {
"lambda-labs-gpu-cloud": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* 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.
Cursor's Agent mode turns Lambda Labs (GPU Cloud) into an in-editor superpower. Ask Cursor to generate code using live data from Lambda Labs (GPU Cloud) and it fetches, processes, and writes. all in a single agentic loop. 7 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.
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 Cursor 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 Cursor via MCP
Follow these steps to integrate the Lambda Labs (GPU Cloud) MCP Server with Cursor.
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
Save the file
Cursor will automatically detect the new MCP server
Start using Lambda Labs (GPU Cloud)
Open Agent mode in chat and ask: "Using Lambda Labs (GPU Cloud), help me...". 7 tools available
Why Use Cursor with the Lambda Labs (GPU Cloud) MCP Server
Cursor AI Code Editor provides unique advantages when paired with Lambda Labs (GPU Cloud) through the Model Context Protocol.
Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context
Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards
MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment
VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools
Lambda Labs (GPU Cloud) + Cursor Use Cases
Practical scenarios where Cursor combined with the Lambda Labs (GPU Cloud) MCP Server delivers measurable value.
Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP
Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically
Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates
Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data
Lambda Labs (GPU Cloud) MCP Tools for Cursor (7)
These 7 tools become available when you connect Lambda Labs (GPU Cloud) to Cursor 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 Cursor
Ready-to-use prompts you can give your Cursor 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 Cursor
Common issues when connecting Lambda Labs (GPU Cloud) to Cursor through the Vinkius, and how to resolve them.
Tools not appearing in Cursor
Server shows as disconnected
Lambda Labs (GPU Cloud) + Cursor FAQ
Common questions about integrating Lambda Labs (GPU Cloud) MCP Server with Cursor.
What is Agent mode and why does it matter for MCP?
Where does Cursor store MCP configuration?
mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.Can Cursor use MCP tools in inline edits?
How do I verify MCP tools are loaded?
Connect Lambda Labs (GPU Cloud) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Lambda Labs (GPU Cloud) to Cursor
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.