TestDino
NewGive your AI agents test context with MCP

Scale the Playwright tests your AI writes

TestDino is a Playwright cloud companion. It records CI runs, detects flakes, and keeps traces and fix workflows ready for teams and AI agents over MCP.

Trusted by teams at
Swatch
Malwarebytes
Deriv
OpenObserve
Keen
Rho
Franklin
Lumin
Debugging

Debug test failures in your browser

Every test run gets a multi-tab report: summary, spec breakdown, error groups, run history, and configuration metadata. Understand any run in 5 minutes.

Flake Management

Find and fix unreliable tests

Every test gets a stability percentage and a root cause category: timing, environment, network, assertion, or other. You see which tests are unreliable and why, not just that something failed again.

Analytics & Trends

Track test health across your suite

Six views in one dashboard: suite summary, test run timing, individual test trends, error categorization, coverage metrics, and environment pass rates. Filter everything by branch, tag, or time period.

CI & Team Integration

Fits into how your team ships code

Add the TestDino reporter to GitHub Actions or GitLab CI. Set pass rate or flaky thresholds on PRs. TestDino posts a status check so code that doesn't meet your bar can't be merged.

Your shards are running. You have no idea what's passing.

Without TestDino

Tests pass. You still don't know.

GitHub Actions
Playwright E2E Tests
#1162
Summary
Jobs
playwright-e2es (1/3)
playwright-e2es (2/3)
playwright-e2es (3/3)
merge-reports
With TestDino

Results stream in as tests run.

TestDino
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Worker 1
Idle
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Start streaming in three steps

Results stream live and stay as history your agents can act on.

  1. 1

    Install the reporter

    npm install @testdino/playwright
  2. 2

    Register the reporter in your config

    playwright.config.ts
    reporter: [
      ['@testdino/playwright', {
        token: process.env.TESTDINO_TOKEN,
      }],
    ]

    Set TESTDINO_TOKEN to a project API key. Generate an API key

  3. 3

    Run your tests

    npx playwright test

MCP server for
AI-assisted debugging

Claude, Cursor, and Copilot can query your test results directly. Ask your AI assistant why a test failed and it pulls real context from TestDino.

Verified reviews on G2

Reviews from teams running Playwright in CI, published on G2.

G2
AI-powered Playwright reporting for analyzing test failures

Analyzing failed Playwright runs in CI used to eat up a lot of our time. TestDino solved that with a centralized dashboard that pulls in screenshots, logs, and failure trends in one place. What's been most useful is the automatic grouping of failures, since instead of checking each failing test individually, we can immediately see patterns and likely causes. It's made triaging failures, and identifying which tests are simply flaky, dramatically faster.

5/5
Yash J.
Yash J.

Lead Software Engineer

G2
Clear visibility into slow and flaky Playwright tests

We inherited an existing test suite without much context on how it was built, and TestDino gave us a real way to take ownership of it. It shows us clearly which tests are the slowest, the flakiest, and the ones failing most often, which has been essential for knowing where to focus our effort. It's given us the visibility to understand the current state of the code and steadily improve its reliability.

4.5/5
Estefania F.
Estefania F.

Senior QA Engineer at Penpot by Kaleidos

G2
Comprehensive dashboard for QA automation

I monitor everything my tests do, from the full list of tests to detailed error screenshots. The GitHub integration is smooth, so commit hashes, CI runs, and HTML reports open straight from the dashboard. I use TestDino almost every day, and it has improved the quality of our automation code.

5/5
Shrinath R.
Shrinath R.

Lead QA Automation Engineer

FAQs

TestDino, also searched as testdino or Test Dino, is a cloud-based companion web app for Playwright that records CI test runs to provide centralized debugging, flaky test detection, and analytics. It is built for both teams and AI agents, making test runs, failures, and fix workflows fully queryable and actionable over MCP and API.