# Mozaika

> Use this tool when you need to create visually consistent and accurate digital products by referencing real-world design examples and decoded design tokens. Mozaika solves the problem of inconsistent design implementation by providing a library of product screens, sections, and design tokens for coding agents to draw from. It takes in design requirements and outputs actionable design references, making it ideal for use cases where design accuracy and consistency are crucial.

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

## Description

Design references for coding agents: real product screens, sections and decoded design tokens.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-07-04

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/design.mozaika%2Fmozaika)

## Use it

MCP endpoint published by the skill: `https://mozaika.design/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": "design-mozaika-mozaika"
    }
  }
}
```

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