Esta IA hace Testing de TODO tu código (en local y produccion)

What TestSprite is

TestSprite is an AI-driven end-to-end testing platform (MCP-style tool) that auto-generates, runs, and records tests for web apps locally and in production. It integrates as an “MCP” into code editors and AI agents so the editor/agent can call TestSprite tooling directly.

Key capabilities / product features

• Auto-generates tests from a short product specification (PRD) or by scanning the project.
• Saves generated tests into your repo (creates a test-sprite-test folder); tests can be tracked with Git.
• Executes tests step-by-step by controlling a browser (Playwright/Selenium style) and supports parallel runs.
• Records detailed step logs and a video of each test run for playback and debugging.
• Visual test-step editor: modify inputs or steps in a recorded run and re-run only that step or subsequent steps.
• Produces machine- and human-readable reports (Markdown/raw report + HTML previews).
• Supports writing tests in a different language than the app (e.g., TypeScript app with tests emitted in Python).
• Continuous integration:
  • GitHub App integration runs tests on PRs, can block merges if tests fail, and re-runs tests on deployment.
• Cloud-run support for testing deployed branches (hosts include Vercel, Netlify, Render, Fly.io).
• Free trial/tier: example mention of 150 credits/month for trying the service.
• API keys authenticate MCP connections from editors and CI.

Tutorial / demo — practical workflow

1. Prepare your app and a dedicated test account (recommend creating an AI/test-only user for login credentials).
2. Create a TestSprite account and generate a named API key.
3. Add TestSprite as an MCP in your editor/agent:
   • Cursor: “Add to Cursor”, paste API key, install; open chat and ask “Help me test this project using TestSprite”.
   • Cloud Code: run the quick install script/CLI, paste API key into the install command, confirm MCP listed.
   • VS Code: use the MCP/add server flow (stdin/stdout server), add TestSprite command in workspace config, paste API key into config, restart workspace; open chat and request tests.
   • Antigravity/other editors: paste the MCP config JSON and API key into the editor’s MCP server management.
4. (Optional) Generate a PRD via AI and upload it to the project (e.g., into a docs folder) so TestSprite knows expected behavior.
5. Run TestSprite from the editor/agent chat or cloud command. It scans the project, generates tests, writes files, and executes them.
6. Inspect results in the dashboard: list of tests, pass/fail status, detailed step logs, and a recorded video per test. Use the UI to edit input values and re-run specific steps.
7. GitHub integration: install the GitHub App, link repo(s), and configure toggles for PR/draft/auto-run/block merging on failures.
8. Deploy branches to supported hosts (Render, Vercel, Netlify, Fly.io) to allow TestSprite to run tests against live environments.
9. Iterate: fix issues, re-run tests locally or via CI; TestSprite will reuse the previously generated test folder.

Examples and findings from the demo app

• Demo app: plant image upload + analysis (uses GPT-4/Gemini models for image interpretation).
• Auto-detected tests included:
  • Landing page load
  • Registration/email validation
  • Login/dashboard
  • Report generation
  • Analysis flow
• Example failures observed:
  • Dashboard rendered charts immediately with no loading placeholder (AI flagged missing skeleton/loader).
  • An analysis/report flow did not reach the final report step (test failed and video showed the failure).
• The presenter used the UI to change an email field value in a registration test and re-ran only that step to validate behavior quickly.

Artifacts produced by TestSprite

• Test folder in repo (test code files).
• Markdown/raw test report (readable in editor preview).
• Per-test step logs and replayable video recordings.
• CI status checks on PRs (pass/fail visible in GitHub).

Notes, recommendations, and constraints

• Create a dedicated AI/test account so credentials can be deleted after testing.
• Restart the editor after MCP install if the MCP doesn’t appear connected right away.
• Tests are generated by scanning the project and the PRD — ensure the PRD accurately describes desired behavior.
• You must deploy the project (to supported hosts) for TestSprite to run GitHub/PR production checks.
• API keys are scoped per environment; you can reuse the same key across editors or create separate keys per tool.

Quick checklist for getting started

1. Create a TestSprite account (get free credits).
2. Create an API key (name it per-editor if desired).
3. Install the TestSprite MCP in your editor/agent (Cursor, Cloud Code, VS Code, Antigravity, etc.).
4. Start your app locally (note port + route) and provide a test account to the tool.
5. Provide or generate a short PRD/spec and upload it to TestSprite.
6. Run tests, review videos/reports, edit steps as needed, fix issues, and re-run.
7. (Optional) Install the GitHub App, enable PR checks, and connect to a deployment host for production checks.

Main speakers / sources

• Presenter / video author: owner/creator referenced by fast.dev (presenter signs off mentioning fast.dev and social links).
• Product / primary source: TestSprite.
• Tools and integrations referenced: Cursor, Cloud Code, VS Code, Antigravity, Trie (editor/agent MCP hosts); GitHub (PR integration); deployment hosts: Render, Vercel, Netlify, Fly.io.