Vynix: Visual Bug Reports for AI Coding Agents

• Point-and-click feedback: Easily capture feedback on any website by simply clicking on elements.
• Multiple capture modes: Supports element selection, text selection, and region capture for detailed annotations.
• Automatic context collection: Gathers element details, DOM and CSS selectors, console errors, and failed network requests with each note.
• Integrated screenshotting: Captures a screenshot with every annotation for visual context.
• AI-ready prompts: Generates prompts compatible with AI coding agents like Claude, Cursor, GitHub Copilot, Gemini, Codex, and more.
• One-click GitHub issue creation: Streamlines the process of reporting bugs by creating GitHub issues directly.
• Flexible export options: Export reports as Markdown, AI prompts, or JSON.
• Team collaboration: Offers read-only review links for seamless team feedback.
• Native MCP server: Allows AI coding agents to directly read feedback for faster resolution.
• Works on all environments: Compatible with staging, development, and production websites.

Vynix provides a visual feedback layer designed for AI coding agents. It simplifies bug reporting by allowing users to click on any element of a live website and instantly generate structured context that AI agents need to fix issues. This eliminates vague reports and screenshots, offering a more efficient and actionable feedback loop for developers, agencies, QA teams, founders, and product managers working with AI-assisted development.

Privacy: Vynix is designed with privacy in mind. It only captures the necessary information for a note and never records sensitive data like passwords, cookies, or authentication tokens. It operates in an isolated Shadow DOM to prevent interference with your website.