DebuggAI | Automated Browser Testing for Pull Requests
DebuggAI helps development teams identify UI issues by automating browser tests during the pull request process. It is designed for teams that want to verify UI functionality before merging code.
At a glance
- Category
- Software Development
- Best for
- Software companies, Development teams, Open source project maintainers, Professional developers
- Pricing
- Paid plans start at $20/month for the Pro tier. A free tier is available for open source projects, and custom pricing is available for Enterprise organizations.
- Key use cases
- Automated PR Verification, Local Dev Validation, Automatic Test Suite Building, Natural Language Browser Testing
- Integrations
- GitHub, Claude, Codex
- Official website
- debugg.ai
DebuggAI provides automated end-to-end browser testing integrated with GitHub. It is designed for software companies and development teams that want to verify UI functionality on every pull request without managing their own testing infrastructure.
The tool uses AI to analyze code diffs and generate targeted tests, which may reduce the need for manual Playwright or Selenium configuration. It handles repository cloning, building, and browser orchestration in a remote environment, posting results, including videos and logs, directly into GitHub comments.
Beyond PR testing, it supports on-demand testing against local development servers via secure tunneling. It also offers an MCP server for those using AI agents like Claude or Codex to trigger browser automation using natural language.
Buyers should confirm if their current workflow relies on specific local environment variables or complex hardware dependencies that might affect remote browser execution.
Key Features
Automatically detects new PRs and runs AI-powered browser tests to verify changes before they are merged.
Posts test pass/fail status, recordings, and debugging insights directly as comments in the GitHub PR thread.
Handles repository cloning, build processes, and browser orchestration so users do not need to configure servers or containers.
Supports testing against localhost by creating a secure tunnel for remote browsers to reach a running local app.
Analyzes code changes to help build test suites that cover edge cases and error handling.
Allows AI agents in platforms like Claude and Codex to run and replay browser tests using natural language.
Use Cases
Running browser tests on pull requests to help catch UI regressions before code is merged.
Validating a user flow against a local development server before committing code.
Using AI to generate test cases based on real usage patterns and code changes.
Using an MCP server to describe a test flow in plain English for an AI agent to execute.
Best For
Integrations
Pricing
Paid plans start at $20/month for the Pro tier. A free tier is available for open source projects, and custom pricing is available for Enterprise organizations.
FAQ
Setup typically takes approximately two minutes via the installation of a GitHub app and a workflow file.
No, DebuggAI handles repository access, builds, and browser orchestration in a remote environment.
There is a free tier for open source, a Pro plan at $20/month, a Grow plan at $40/month, and custom pricing for Enterprise.
Test results, including pass/fail status and recording links, are posted as comments on GitHub pull requests.
Source category: Software Development
Source subcategory: Test Automation
