ForgeQA AI
# ForgeQA AI
ForgeQA AI is a licensed, locally run Playwright end-to-end testing MCP server for Claude Desktop and Cursor. It helps AI coding agents inspect semantic accessibility structure, validate role-based browser workflows with explicit outcome assertions, and compile reviewed flows into reusable Playwright specifications.
## Tools
- `scan_dom_accessibility` opens a supplied URL in a fresh headless Chromium session and returns a structured accessibility-tree snapshot with meaningful roles, names, and states.
- `dry_run_qa_flow` executes role-based browser interactions and outcome assertions, then returns a step-by-step pass/fail report.
- `compile_playwright_spec` converts reviewed actions and assertions into a reusable Playwright E2E specification in the local `tests` directory.
## Supported interactions and assertions
- Click, fill, check, select options, and press keys.
- Verify visible and hidden elements.
- Verify exact or partial text.
- Verify input values and checked states.
- Verify final URL outcomes.
## Requirements
- Node.js 20 or newer. Use the current Node.js LTS release.
- Claude Desktop or Cursor with MCP support.
- Playwright Chromium 1.63.0.
- A ForgeQA AI license key delivered after purchase.
Install the matching Chromium runtime once:
```bash
npx -y playwright@1.63.0 install chromium
```
## Purchase
ForgeQA AI is available as a $79 one-time purchase:
[Purchase ForgeQA AI](https://lajuanetorrey.gumroad.com/l/forgeqa-ai)
The purchase includes the npm package, setup guide, and a unique Gumroad license key.
## Claude Desktop and Cursor configuration
```json
{
"mcpServers": {
"ForgeQA": {
"command": "npx",
"args": ["-y", "@ltorrey/forgeqa-mcp@1.1.0"],
"env": {
"GUMROAD_LICENSE_KEY": "YOUR_GUMROAD_LICENSE_KEY"
}
}
}
}
```
The MCP server uses stdio and runs locally through Node.js and Chromium.
### Claude Desktop paths
- macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
- Windows: `%APPDATA%\Claude\claude_desktop_config.json`
### Cursor paths
- Global: `~/.cursor/mcp.json`
- Project-specific: `<project-root>/.cursor/mcp.json`
## Privacy and safe use
ForgeQA AI contains no product telemetry. At startup, it sends the Gumroad product ID and license key to Gumroad for validation. It does not log or persist the key. Test inputs and browser activity run locally, while target websites receive ordinary browser requests.
`dry_run_qa_flow` performs real browser interactions. Use ForgeQA AI only on applications and environments you are authorized to test. Prefer staging environments and disposable test data for flows that submit forms or change server-side state. Review generated specifications before running them.
## Licensing, support, updates, and refunds
- Each purchase provides a unique license key that must not be shared or published.
- Configuration examples pin version 1.1.0 so updates cannot silently change behavior. Review release notes before changing versions.
- For support, reply to the Gumroad receipt or use the creator contact on the product page. Never send a complete license key in a support message.
- Sales are final. Refunds are not offered except where required by applicable law or Gumroad's mandatory policies.
## Disclaimer
ForgeQA AI is testing infrastructure, not a guarantee that an application is defect-free. Review generated specifications and test results before relying on them in a release decision.
This repository contains public registry metadata and installation instructions. The licensed implementation is distributed through npm.
## Registry inspection mode
`npm run start:glama` starts a restricted MCP runtime for automated registry inspection. It publishes the same public tool names, descriptions, schemas, and safety annotations as ForgeQA AI, but every tool call is rejected. It cannot scan pages, run QA flows, or generate test files, and it does not bypass product licensing.
Copyright 2026 Lajuane Torrey. All rights reserved.
TDQS
Scored across 3 tools
The three tools are largely distinct: one scans the accessibility tree, one executes a QA flow in the browser, and one writes a Playwright spec. dry_run_qa_flow and compile_playwright_spec both consume role-based actions and assertions, so an agent could initially confuse execution with persistence, but the descriptions clarify the difference.
All tool names follow a consistent snake_case verb_noun pattern: scan_dom_accessibility, dry_run_qa_flow, and compile_playwright_spec. The naming is predictable and action-oriented.
Three tools is a tight, well-scoped set for an AI-assisted QA server. Each tool maps cleanly to a distinct stage in the workflow: inspect, validate, and generate.
The core QA workflow is covered: accessibility scanning, flow verification, and spec generation. Minor gaps exist, such as no tool for listing or updating compiled specs, but these are workable for most use cases.