Markloop

Markloop is a web app that closes the feedback loop for HTML documents created by AI coding agents. Designed for product managers, engineers, consultants, and anyone whose agent drafts specs, reports, proposals, or technical docs, Markloop solves the problem of scattered feedback and manual copy-pasting. Instead of pasting agent output into Google Docs or Slack—where formatting breaks and comments get lost—teams use Markloop to share rendered HTML artifacts, pin comments to exact sections, embed questions for reviewers, and export the structured feedback back to the agent over MCP or as plain files.

What Makes Markloop Stand Out

• Anchored comments: Reviewers pin feedback to a specific paragraph, sentence, or code block. Comments stay attached to the version they were made on, preserving context across revisions.
• Agent-ready package: Every comment exports with its CSS selector, quoted text, and note—ready for the agent to apply in one pass. No manual translation into prompts.
• MCP integration: Native support for Claude Code and Codex lets agents push documents and pull feedback directly from the terminal. Other agents can consume the same feedback as plain files.
• Version tracking with resolution: Each upload becomes a new version. Comments are marked as addressed or open, so the team and agent know exactly what changed between iterations.
• Unlimited free reviewers: Clients and teammates can comment and answer questions at no cost. Only creators (users who upload and manage projects) need a paid seat.

Who Should Use Markloop

• Product managers and founders who need sign-off on AI-drafted PRDs and specs, without losing context in email threads.
• Engineering teams reviewing RFCs, architecture docs, and migration plans generated by coding agents—with the ability to track resolved comments across versions.
• Consultants and agencies sharing polished HTML reports and proposals with clients, collecting feedback in a single, scoped workspace.

Frequently Asked Questions

What is Markloop?

Markloop is a review platform for HTML documents created by AI agents. It lets you share rendered artifacts, collect comments and answers in context, and send structured feedback back to your agent for application.

How does Markloop work with AI agents?

Markloop connects natively via MCP (Model Context Protocol) with agents like Claude Code and Codex. Agents push documents to a project and pull feedback as structured files. For other agents, feedback exports as plain text files that can be processed programmatically.

What are the limitations of Markloop?

Markloop is designed for self-contained HTML artifacts—not live websites or multi-page web apps. It focuses on the review loop for documents, not on real-time collaboration or editing. Reviewers cannot edit the source file; they can only comment and answer questions.