#758 · Primary category: AI Agents & Automation

agent-qa

ai-agents ai-testing anthropic autonomous-agents browser-automation chatgpt claude-code clawdbot codex developer-tools dsh-plugin end-to-end-testing frontend mcp mcp-server mcp-tools model-context-protocol openai playwright qa-automation

Open-source self-improving QA agent for software teams. A test harness with memory. Write tests in natural language for web and mobile. agent-qa learns from every run, adapts to UI changes, and catches regressions before you ship.

Project last updated:08/03/26

GitHub Stars

935

Forks

15

Contributors

4

License

Apache-2.0

Why we included this project

The usual cost of UI testing is upkeep: selectors break the moment the design shifts. agent-qa bets on a different approach, where your team writes the test in plain English for web or mobile and the agent works out the concrete actions against the live page. When a click or fill fails mid-run, the harness re-observes the screen and retries a different path in the same run instead of dying on the first broken step, which is what makes suites survivable as the interface drifts. A memory layer compounds the benefit by carrying what it learned from each healed step into later runs, so fixes tend to stick rather than repeat. Developers get a dashboard and CLI, coding agents can drive the same suite through its MCP and skills, and sandboxed hooks let you seed fixtures or call APIs from inside Docker containers before a test executes. If you are maintaining flaky, Playwright-based UI tests, this is worth a look.

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