# Hyperbolic GPU

> Use this tool when you need to access on-demand GPU compute resources for AI and machine learning workloads, or require scalable cloud management for remote command execution and instance provisioning. It solves problems of limited local compute capacity, enabling discovery, rental, and management of decentralized GPU instances with detailed hardware specifications. With real-time marketplace querying and automated instance management, it provides a seamless interface for inputs like rental requests and outputs like JSON responses, ideal for AI researchers, developers, and automated workflows.

Canonical page: https://skillsregistry.net/skills/hyperbolic-gpu  
JSON: https://api.skillsregistry.net/v1/skills/hyperbolic-gpu

## Description

This MCP server provides GPU cloud management and SSH connectivity for Hyperbolic's decentralized GPU network, enabling AI assistants to discover available GPU instances, rent compute resources, and execute remote commands on rented hardware. Built by Hyperbolic Labs using TypeScript with the MCP SDK, node-ssh, and direct API integration, it features real-time GPU marketplace querying with detailed hardware specifications (VRAM, CPU cores, RAM, storage), automated instance provisioning with startup delays, SSH connection management with private key authentication, and remote command execution capabilities. The implementation includes comprehensive instance lifecycle management from rental to termination, connection status monitoring, and structured JSON responses for all operations, making it valuable for AI researchers needing on-demand GPU access, developers requiring scalable compute for machine learning workloads, and automated workflows that need to provision, configure, and manage cloud GPU resources programmatically.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** iot-hardware
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/hyperbolic-gpu)
- **Repository:** <https://github.com/hyperboliclabs/hyperbolic-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "hyperbolic-gpu"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/hyperbolic-gpu` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/hyperbolic-gpu/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt