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Maestro made mobile flows simple. agent-qa makes them learn.

Maestro popularized YAML-declared mobile UI flows with static commands. agent-qa keeps the YAML ergonomics but replaces static commands with AI-executed intent, plus web support and memory.

Try agent-qa, the source-available QA agent where mobile flows compound into memory.

agent-qa vs Maestro

Capabilityagent-qaMaestroDetails
YAML-based authoringBoth use YAML. Maestro's YAML lists UI commands (tapOn, assertVisible); agent-qa's YAML states user intent in plain English that the runtime plans against the live app.
Survives UI changesMaestro's text/ID matching tolerates small shifts but static commands still break on real redesigns. agent-qa re-plans the whole step from intent.
Execution memoryagent-qa records behavioral observations across runs; Maestro flows execute the same commands cold each time.
Source accessMaestro is open source and pairs with a paid cloud for scaled execution. agent-qa is source available under FSL-1.1-ALv2, and its full workflow stays repo-local.
Web testing in the same harnessMaestro is mobile-first with some web support. agent-qa treats web and mobile as equal targets under one contract.
Coding-agent nativeagent-qa ships MCP tools, Skills, and structured evidence for autonomous agents; Maestro is operated by humans and CI scripts.
Bring your own LLMagent-qa's planning runs on the model provider you configure. Maestro's core doesn't use LLM planning.
Local and CI executionBoth run locally and in CI without mandatory cloud services.

Why Maestro users graduate to agent-qa

Intent beats commands

Maestro's tapOn and assertVisible commands are simpler than code, but they still encode a fixed UI. agent-qa's steps say what the user is doing, 'add the item to the cart and check out', and the runtime works out the taps on whatever the screen looks like today.

The same YAML instinct, more leverage

If your team already thinks in Maestro YAML, agent-qa feels native on day one, the file just says more with less, covers web too, and every run feeds memory and cache instead of evaporating.

No cloud dependency for scale

Maestro's scaled execution story leads to its paid cloud. agent-qa's runs, artifacts, memory, and dashboard are local and CI-native, scale is your infrastructure decision, not a subscription tier.

Maestro proved YAML flows are the right ergonomics for mobile testing. agent-qa keeps the ergonomics and upgrades the engine: intent instead of commands, memory instead of amnesia, and web included.

Frequently asked questions

Is agent-qa a good Maestro alternative?

Yes. It's the natural next step. You keep YAML-declared flows and gain AI execution that survives redesigns, memory that compounds across runs, first-class web support, and MCP/Skills integration for coding agents.

What does agent-qa cost compared to Maestro?

Maestro is free and open source, and monetizes scaled cloud execution. agent-qa is source available under FSL-1.1-ALv2 with no paid tier or license fee for FSL-permitted use. agent-qa's operating cost is LLM tokens on your chosen provider, moderated by caching.

How do I migrate Maestro flows to agent-qa?

It's the friendliest migration on this site: your Maestro YAML already names each flow's steps, so rewriting command sequences as plain-English intent is nearly mechanical, and the result is shorter than what it replaces.

Does agent-qa support Android and iOS like Maestro?

Yes, native flows on both platforms, plus web, all under the same YAML contract, memory store, and CLI.

Why does memory matter for mobile testing?

Mobile apps change UI constantly and devices add timing variance. agent-qa's memory records how your app actually behaves, screens, quirks, flows, so subsequent runs plan faster and flake less, which static command flows can never do.

Sources

This page is based on public product and documentation sources. Verify current features and pricing with each vendor before making a purchase decision.

Where agent-qa pulls ahead of Maestro

The parts of agent-qa that answer what Maestro leaves you carrying.

Natural-language tests

Describe actions and assertions in natural language. agent-qa resolves them against the live interface using visible roles, labels, and screen state.

Learn about natural language tests

Natural-language YAML

Write the behavior and expected outcome in plain English. The test stays as reviewable YAML in your repository.

Targets users recognize

Refer to “New issue,” “Checkout,” or the “Issues table.” agent-qa finds the matching control in the live interface.

One format, every surface

Use the same natural-language structure across web, Android, and iOS without maintaining selector-heavy variants.

Execution memory

A run that passes leaves evidence: elements that resolved, a flow that worked, and timings that are real. agent-qa distils that evidence into durable facts, procedures, cautions and measurements. Each becomes a reviewable bundle committed next to your tests. Nothing steers a run until the evidence says it should, and once it does, the next run replays what already works instead of deriving it again.

Learn about memory

Bundles you can review

Each thing learned is a directory in your repository: the record, the evidence behind it, and the artifacts that justify it. Read it in a pull request.

Proven before it is used

New knowledge is born a candidate. Offline replay and attributed evidence from live runs decide whether it ever reaches a planner.

Warm runs get faster

A flow that already worked is replayed rather than re-derived, and stale facts are superseded instead of quietly served.

Web, Android, and iOS

Point the same natural-language flow at a web target, an Android build, or an iOS build. Playwright and Appium are execution kernels here, not code generators: no test script is ever produced. The agent decides on each action from what it can currently see, and the kernel performs it, whether that is a click in Chromium, a tap on a local emulator, or a gesture on a remote device.

Learn about mobile testing

Execution kernels

Playwright and Appium only perform the actions the agent decides on. No test script is generated, and nothing is replayed from a recording.

Three web engines

Run the same flow on Chromium, Firefox, or WebKit, and override the engine, viewport, or headless mode per test.

Native and remote devices

Drive real Android and iOS builds by app package or bundle ID, on a local emulator, a simulator, or a remote device.

Self-healing execution

When a sub-action fails, because the click was intercepted, the control moved, or the field will not take the value, agent-qa re-observes the screen and plans another route to the same step, inside the same run. What it will not do is find another step: a recovery has to reach what you asked for, so a route to a different outcome is declined rather than taken, and the run fails with the reason it found.

Learn about self-healing

Re-observe, then re-plan

A failed sub-action is not retried. The screen is read again and the next attempt is planned against what is actually on it.

Bounded by the step

A recovery has to reach what the step asked for. A route that would reach a different outcome is declined, not taken.

The trace stays honest

Every attempt is recorded: what failed, what was tried, and what was refused. A healed step never reads as a clean one.

* This comparison is based on publicly available information. Product capabilities and pricing can change; verify details with each vendor before making a purchase decision.