# co.fastgpu/fastgpu

> co.fastgpu/fastgpu — co-fastgpu-fastgpu. Use this tool when you need to optimize GPU cloud rental costs by comparing live prices across providers and matching workloads to the most affordable option, saving time and resources in the process. It takes in workload requirements as input and outputs the cheapest GPU provider, streamlining the decision-making process. Ideal for users seeking to reduce expenses on GPU-intensive tasks, such as machine learning, gaming, and video rendering.

Canonical page: https://skillsregistry.net/skills/co-fastgpu-fastgpu  
JSON: https://api.skillsregistry.net/v1/skills/co-fastgpu-fastgpu

## Description

Compare live GPU cloud rental prices and match workloads to the cheapest provider.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-13

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/co.fastgpu%2Ffastgpu)

## Use it

MCP endpoint published by the skill: `https://fastgpu.co/api/mcp`

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": "co-fastgpu-fastgpu"
    }
  }
}
```

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