Founder, Vynix

Suraj Sharma • Peerlist

<h3>Vynix: Visual Bug Reports for AI Coding Agents</h3><ul><li>Point-and-click feedback: Easily capture feedback on any website by simply clicking on elements.</li><li>Multiple capture modes: Supports element selection, text selection, and region capture for detailed annotations.</li><li>Automatic context collection: Gathers element details, DOM and CSS selectors, console errors, and failed network requests with each note.</li><li>Integrated screenshotting: Captures a screenshot with every annotation for visual context.</li><li>AI-ready prompts: Generates prompts compatible with AI coding agents like Claude, Cursor, GitHub Copilot, Gemini, Codex, and more.</li><li>One-click GitHub issue creation: Streamlines the process of reporting bugs by creating GitHub issues directly.</li><li>Flexible export options: Export reports as Markdown, AI prompts, or JSON.</li><li>Team collaboration: Offers read-only review links for seamless team feedback.</li><li>Native MCP server: Allows AI coding agents to directly read feedback for faster resolution.</li><li>Works on all environments: Compatible with staging, development, and production websites.</li></ul>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.

VYnix Chrome Extension

<h3>Empower your AI agents with the full context behind every website issue.</h3>The Vynix MCP server bridges the gap between visual website feedback and AI coding assistants like ChatGPT, Claude, Cursor, VS Code, and Codex. It allows these agents to understand and act upon detailed annotations, run diagnostics, update issue statuses, and even create GitHub issues, all with complete context.<ul><li>Connect your AI agent: Seamlessly integrate with popular AI tools through hosted OAuth or a local NPX server. Access is revocable and clearly distinguished between read and write actions.</li><li>Ask your agent what needs fixing: Start with real, open feedback. The agent can list projects and annotations, providing precise details instead of relying on vague descriptions.</li><li>Full context, not just a screenshot: Every annotation includes the exact element, DOM, runtime evidence, and discussion history, enabling your agent to understand the issue accurately. It also provides region screenshots, console errors, and failed network requests.</li><li>Diagnose the root cause: Request a diagnosis and receive ranked root causes, a confidence score, and identification of the most likely files to modify.</li><li>Act and close the loop: Update annotation status, add comments, open GitHub issues with pre-filled prompts, or generate shareable review links. All write actions are clearly flagged for your confirmation.</li></ul>Vynix MCP offers 17 tools covering the entire feedback loop: discover, understand, and act. It supports read, write, and external-action tools, ensuring transparency and control over every AI-driven task.

Vynix MCP Server

<h3>Vynix is a powerful tool designed to bridge the gap between visual website feedback and actionable context for AI coding agents. It transforms simple point-and-click feedback on live websites into structured data that AI agents can immediately understand and act upon. This includes precise element identification, DOM structure, console logs, and network requests, all delivered through a native Model Context Protocol (MCP) server.</h3><ul><li>Effortless Feedback Capture: Point at any element or drag to select a region on your live site. Vynix highlights the target and captures its details automatically.</li><li>Structured Context: Instead of vague descriptions, Vynix provides exact CSS selectors, XPath, DOM snippets, computed styles, viewport information, console errors, and failed network requests.</li><li>AI Agent Integration: Supports multiple AI agents like Claude, CodeCursor, GitHub Copilot, Windsurf, and Gemini. Feedback can be delivered as a clean Markdown report or live via MCP.</li><li>Zero Runtime Dependencies: The Vynix widget is lightweight (under 16KB gzipped) and integrates seamlessly into any stack without affecting performance.</li><li>Multiple Installation Options: Easily install via a script tag or a browser extension.</li><li>AI Diagnosis: Vynix can diagnose issues by analyzing the captured page, element, DOM, and runtime errors, providing ranked root causes, confidence scores, and suggested fixes.</li><li>Enhanced Privacy: Captures only necessary metadata, strips query strings, and offers options to disable diagnostics entirely.</li><li>Seamless Workflow: Consolidate multiple annotations into a single batch for export to Markdown, AI prompts, or JSON.</li><li>Flexible Export Formats: Choose between human-readable Markdown reports, imperative AI prompts, or structured JSON.</li><li>Native MCP Server: Enables AI agents to read, clarify, and resolve annotations live without copy-pasting, improving efficiency.</li></ul>