# SuperComponents Server

> Use this tool when you need to automate component generation and streamline design implementation. The SuperComponents Server analyzes designs, generates components, and creates implementation instructions, solving problems related to manual component creation and design optimization. It takes design inputs and produces generated components and instructions as output, ideal for use cases where efficient and accurate component generation is crucial.

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

## Description

MCP server for AI-powered component generation - analyze designs, generate components, and create implementation instructions.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ei92fdeqcw)
- **Repository:** <https://github.com/SuperComponents/SuperComponents>

## 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": "supercomponents-supercomponents"
    }
  }
}
```

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