# mini-creative-toolkit

> mini-creative-toolkit — furkiozknn-mini-creative-toolkit. Use this tool when you need to efficiently process media files without relying on external networks or paid APIs. The mini-creative-toolkit provides 23 CPU-first media tools for tasks such as background removal, image resizing, and video trimming, with a focus on offline processing and minimal dependencies. Ideal for use cases where network independence and cost-effectiveness are crucial, with inputs including various media file types and outputs ranging from resized images to trimmed videos.

Canonical page: https://skillsregistry.net/skills/furkiozknn-mini-creative-toolkit  
JSON: https://api.skillsregistry.net/v1/skills/furkiozknn-mini-creative-toolkit

## Description

23 CPU-first media tools behind one MCP server: background removal, EXIF/GPS stripping, resize, thumbnails, GIFs, video trim. 22 of them report "network": "none" in their own response payload rather than in a README, and a test fails if any other module ever imports an HTTP client. No GPU, no paid API. 326 tests.

## Trust

- **Trust score (0–1):** 0.62
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Furkiozknn/mini-creative-toolkit)

## 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": "furkiozknn-mini-creative-toolkit"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/furkiozknn-mini-creative-toolkit` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/furkiozknn-mini-creative-toolkit/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