# Hyperbolic GPU MCP Server

> Use this tool when you need to access and utilize GPU cloud resources for compute-intensive workloads, such as machine learning, data analytics, and graphics rendering. It enables users to interact with Hyperbolic's GPU cloud through natural language commands, allowing for easy management of GPU instances and SSH connections. Ideal for use cases requiring scalable, on-demand GPU processing power.

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

## Description

Enables interaction with Hyperbolic's GPU cloud, allowing users to view available GPUs, rent instances, establish SSH connections, and run GPU-powered workloads through natural language commands.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/zxwmzv6lbr)
- **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": "hyperboliclabs-hyperbolic-mcp"
    }
  }
}
```

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

---
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