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Bugster

Bugster is an AI-powered end-to-end testing platform that runs automated tests in real browsers on every pull request. AI agents generate and maintain zero-maintenance E2E tests from plain English descriptions.

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Description

Bugster runs automated end-to-end tests in real browsers on every pull request, using AI testing agents that click, type, and navigate like a real user. There are no fixed scripts or selectors: users describe what to test in plain English and the agents generate and execute the tests, prioritizing changes detected from PR diffs so the most relevant flows are covered first.

Tests are self-maintaining and auto-update across pull requests, and typically run in under a minute in parallel on real browsers in the cloud. Bugster is code-aware through a GitHub App and CLI, works locally, on staging, and on CI platforms such as Vercel and Railway, and can catch UI breaks, broken flows, auth issues, missing elements, and edge-case regressions. When tests fail, it produces detailed bug reports with reproduction steps and video recordings.

Developers can pull tests locally as human-readable YAML, edit them in Cursor or Claude Code, and push changes back, while QA and product teams create tests in the web app using natural language. Data is handled with encryption in transit and at rest, Bugster never accesses or stores source code, and customer data is never used to train AI models. Plans start free ($0), with paid tiers at $20 and $99.

Bugster's Core Features

  • AI agents run E2E tests in real browsers on every pull request

  • Plain-English test creation with no scripts or selectors

  • Zero-maintenance, self-updating tests across PRs

  • PR diff-aware prioritization of changed flows

  • GitHub App and CLI integration for code-aware testing

  • Runs locally, on staging, and on CI (Vercel, Railway)

  • Detailed bug reports with reproduction steps and video recordings

  • Human-readable YAML tests editable in Cursor or Claude Code

How to use Bugster?

  1. Connect your repo: Install the GitHub App and link your repository for automated testing.

  2. Describe tests: Use plain English in the web app or CLI to describe the user flows to test.

  3. Run on PRs: Let AI agents generate and run E2E tests in real browsers on every pull request.

  4. Review failures: Get bug reports with reproduction steps and video recordings when tests fail.

  5. Sync and edit: Use bugster pull and push to manage tests as YAML in Cursor or Claude Code.

Bugster's Use Cases

  • Pull request testing
  • Zero-maintenance QA
  • Cross-environment testing
  • Bug reproduction
  • Migrating test suites

FAQ from Bugster

Bugster Reviews

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