AI testing agents for web apps

An AI testing agent is a program that uses your app the way a person would, then tells you what went wrong. Here is how they work, how to tell good ones apart, and where they fit next to the tests you already have.

5 agents try to .

First test freeRun it from your coding agent

What is an AI testing agent?

An AI testing agent opens your web app in a real browser, reads the screen, and decides what to click and type to finish a task, then reports what broke and where it got stuck. Mimiq runs many at once, each acting as a different one of your users, and adds what the browser records: errors, failed requests and slow requests on your site.

One tester is not your users

A single testing agent is a polite, competent user: it reads every label, fills every field correctly and rarely gives up. Your users are not like that. Some are on a phone, some skim, some type a website without "https", some quit at the second form. A crowd of agents that each play a different user finds the problems a single tester walks straight past.

Each agent acts as a different user with a reason to be there.
They click, type, fill in forms and read their own verification emails.
The browser records errors, failed and slow requests on the step they happened.
Problems are ranked by how many agents hit them.
Run from the app, a coding agent, or CI.

How it works

01
Give it a link and a task
Paste a public address, such as a preview deployment or staging, and say in plain words what a user would try, like "Sign up and start using it". No test scripts and no selectors.
02
Pick how many agents
1, 3, 5, 10 or 20 agents, 5 by default. Each acts as a different one of your users and gets its own real browser for up to 40 steps. About 5 minutes for up to 3 agents, about 5 to 15 minutes for 5, and about 15 to 30 minutes for 20. Agents take turns on shared browsers, so it can take longer when other runs are going, and you can close the tab and come back.
03
Read what they hit
The report shows what broke, what the browser caught on your site (JavaScript errors, requests that failed or answered 4xx or 5xx, and requests slower than 3 seconds), where each agent got stuck or gave up and why in its own words, with the step and a screenshot, and the problems ranked by how many agents hit them, each with a suggested fix.
04
Fix it and run the same agents again
Rerun on the fixed build and see whether the problem is gone for everyone who hit it. Or let your coding agent do the loop through the MCP server, or let the GitHub Action do it on every preview deploy.

How to tell testing agents apart

Ask four questions. Does it use your real app in a real browser, or a model of it? Does it report what the browser recorded, or only what the agent guessed? Does it vary who the agent is, or send one generic tester? And can it run where you already ship, on every preview deploy?

Mimiq answers yes to all four: real browsers, the browser's own records next to the agent's words, a different user per agent, and an MCP server plus a GitHub Action.

Testing agents next to your other tests

Unit tests check functions. End-to-end scripts check the paths you wrote down. Testing agents check what happens when someone new uses the app with no script at all. They overlap least with the tests you have, which is why they find different problems.

Agents are simulated users. They find problems fast and on every build; they do not forecast how many real people will convert, they are not a deterministic regression suite, and they do not install native mobile apps.

From your coding agent

If an AI wrote the change, an AI can try it before you review the diff. Add the MCP server to Claude Code, Cursor or Codex and put two lines in CLAUDE.md or AGENTS.md so it runs on every user-facing change:

## Before calling a user-facing change done
After changing anything a user goes through (signup, onboarding, checkout,
settings, a new feature), run mimiq.test_flow on the preview URL with the task
a user would try. Fix what the agents hit, then run it again. Ask me before
using more than 25 credits.

40steps at most for each agent, each in its own real browser. Every step comes with a screenshot and what the agent was thinking at the time.

20agents at once, each acting as a different one of your users. The browser also records every error, failed request and request slower than 3 seconds on your site, on the step it happened. Agents find problems; they do not forecast how many people will convert.

$0for your first test, with a free account (Google sign-in, no card). It includes 50 credits, enough for 10 agents. After that an agent uses 5 credits, and packs start at $9 for 120 credits.

See a sample report

Questions

Are the agents real people?

No. They are AI agents acting as users, always labeled simulated. They find problems; they do not tell you how many real people will convert.

How many agents should I run?

Three is enough to catch something everyone hits. Five to ten shows which problems are common. Up to 20 at once.

Do they handle email verification?

Yes. Each agent gets an email address with a working inbox, so verification codes and magic links reach it.

What stops them?

CAPTCHAs and bot protection can. Any agent stopped by one is marked as blocked by the site, and if it stops every agent, the run fails and nothing is charged. A staging or preview address without bot protection works, as long as it is public or you give access.

Keep reading

Let the agents find what breaks first.

Your first test is free: sign in with Google and it starts right away. Last checked 2026-10-22.