Enables the use of OpenAI's language models for test execution and planning.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Your AI QA engineer, with memory. Describe a user journey in plain language. agent-qa tests it on web, Android or iOS and keeps the evidence. Use the CLI, the dashboard, or your coding agent through MCP and skills.
memidex: remembers facts and working procedures as reviewable files in your repository.
Self-improvement: validates lessons from runs, retires stale knowledge, and uses your feedback to correct mistakes.
Benchmark | Rank | Published result |
#1 | 100% pass@1 (116/116 tasks) | |
#1 | 99.6% completion (114.5/115 points) |
Read the full benchmark reports, with run evidence and methodology, on our blog. Both used gpt-6-sol with memory and self-improvement off; AppControlBench gives half credit for partial completion.
Inspect a failure. The demo catches a cart showing $29 instead of $53, with the failed step and its screenshot side by side.
See what memory contributed. Inspect the knowledge supplied to a run and trace it back to the steps that used it.
Run from your terminal. Real output from the demo suite: checkout passes; the deliberate cart-total bug fails.
Related MCP server: QAcito
Requires Node.js 24+.
npm install -D agent-qa
npx agent-qa initFollow the quickstart to connect a model and run the demo, or set up with your coding agent.
Early stage. Expect bugs.Report an issue when something breaks.
This server cannot be deployed
Browser-based QA for AI-built software. Test pages with real browsers via agents.
Self-healing CI tests and proof of work for AI agents
Agentic AI quality engineering: run, debug and triage tests on real browsers and devices
Visual testing for coding agents: your agent sees every UI change it makes and triages each diff.
