# Autonomous QA Engineer MCP

> Autonomous QA Engineer MCP — golffycoding-auto-qa-engineer-mcp. Use this tool when you need to automate quality assurance tasks for projects, as it provides a comprehensive workflow for scanning, testing, and diagnosing issues across various platforms. It generates deterministic test suites, executes them, and proposes fixes, streamlining the QA process and reducing manual effort. Ideal for use cases where efficient and reliable testing is crucial, such as in software development and deployment.

Canonical page: https://skillsregistry.net/skills/golffycoding-auto-qa-engineer-mcp  
JSON: https://api.skillsregistry.net/v1/skills/golffycoding-auto-qa-engineer-mcp

## Description

Provides MCP tools that give LLM agents a full QA engineer workflow: scanning projects, generating deterministic test suites, executing them across browser/API/mobile, diagnosing failures, and proposing fixes that require human approval.

## Trust

- **Trust score (0–1):** 0.57
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** browser-automation
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/p15ichxzzb)
- **Repository:** <https://github.com/GolffyCoding/Auto-QA-Engineer-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": "golffycoding-auto-qa-engineer-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/golffycoding-auto-qa-engineer-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/golffycoding-auto-qa-engineer-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