# autousers

> Use this tool when you need to evaluate user experience (UX) with AI-driven testing, leveraging AI personas and human raters to assess usability and gather feedback directly from MCP-aware clients like Claude and ChatGPT. It solves problems related to UX validation, providing actionable insights to improve product design and user interaction. With autousers, you can input design prototypes and output actionable feedback and usability scores.

Canonical page: https://skillsregistry.net/skills/autousers-ai-mcp  
JSON: https://api.skillsregistry.net/v1/skills/autousers-ai-mcp

## Description

Evaluate UX with AI personas and human raters directly from MCP-aware clients like Claude and ChatGPT.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/um85ltbqmk)
- **Repository:** <https://github.com/autousers-ai/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": "autousers-ai-mcp"
    }
  }
}
```

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