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Automate QA with generated scenarios, Playwright tests, execution, and GitHub bug reports.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "qa-ai-mcp-server-gits" yet — see the docs or source repo.
Based on this checkout page feature description, generate end-to-end test scenarios, identify key Playwright locators, and output runnable TypeScript test code. Focus on successful checkout, promo codes, payment failure, and form validation.
A set of core and edge-case test scenarios, locator suggestions, and executable Playwright TypeScript code.
Run the existing Playwright test suite, summarize failing cases, explain the failed steps, error messages, and likely causes, then rank them by severity.
A test execution report with failed cases, error summaries, cause analysis, and priority recommendations.
For the failed cases in this automation run, create a GitHub issue for each high-priority problem, including reproduction steps, expected result, actual result, log summary, and links to related test files.
Well-structured GitHub bug issue drafts or created issue lists for faster engineering follow-up.
Run browser-based web app QA tests with Playwright and generate reports.
Read Jira and Confluence to generate QA artifacts and coverage analysis.
Discover APIs from codebases, run tests, and generate role-based QA audit reports.
Run local QA checks for APIs, test cases, errors, and SLA evaluation.
Run reusable Playwright tests on live deployments with screenshots and structured results.
Analyze and fix test failures with plain-language guidance in IDE and Slack.