Overview
Markloop is a web application designed to close the feedback loop between AI coding agents and human reviewers. Founded by a solo builder, the platform allows users to upload HTML documents generated by agents like Claude Code and Codex, share them with reviewers for contextual comments and answers, and then export the structured feedback back to the agent for automated application. Markloop targets developers, product teams, consultants, and agencies who rely on AI agents to produce specs, reports, proposals, and technical documentation. The service is headquartered online with a global user base and launched in 2025.
Services & Expertise
Markloop offers a focused set of capabilities centered on document review and agent integration:
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Anchored Comments: Reviewers can pin comments to specific sections or sentences within an HTML document. Comments remain attached to the exact version they were made on, preserving context across revisions. This is built for dense specs and technical docs where precision matters.
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Agent-Ready Feedback Package: Every comment is exported with its CSS selector, quoted text, reviewer intent, surrounding context, and version number. The package can be consumed by AI agents over MCP (Model Context Protocol) or as plain markdown files, eliminating manual copy-pasting.
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MCP Integration for Claude Code and Codex: Native MCP support allows agents to push new document versions and pull feedback directly from the terminal. This creates a seamless loop: agent writes, human reviews, agent applies changes.
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Version Tracking: Each upload becomes a version in a chain. Comments are tied to the version they were made on, and new revisions can mark comments as addressed. This provides clear audit trails for iterative review cycles.
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Unlimited Reviewers: All plans include unlimited reviewers at no extra cost. Reviewers can be invited to projects or given read-only links to individual files, with optional expiry and version access controls.
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Read-Only Sharing: Documents can be shared as private or public read-only links. Reviewers see the rendered HTML in the browser, not the source file, preserving control over the original artifact.
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Questions and Decisions: Users can embed open questions directly into documents. Reviewers answer in context, and the answers are included in the feedback package sent back to the agent.
How They Work
The Markloop workflow follows a five-step loop: Add, Share, Collect, Pull, Apply. Users start by uploading an HTML document or having their agent push it via MCP. They then invite reviewers to a project or share a read-only link. Reviewers comment on specific parts of the document and answer embedded questions. The user or their agent pulls the structured feedback package over MCP or as files. The agent applies changes locally and publishes a new version, which can trigger another review round. The entire process is designed to minimize manual handoffs and keep feedback anchored to the original document.
Ideal Client Profile
Markloop is best suited for:
- A solo developer using Claude Code or Codex to draft technical specs who needs stakeholder sign-off without leaving the terminal.
- A product team that generates PRDs and feature proposals via AI agents and requires structured feedback from engineering and design.
- A consultant or agency producing client deliverables like audit reports or proposals in HTML, who wants clients to comment in context without accessing source files.
- An engineering team reviewing RFCs and architecture documents written by agents, needing versioned comments and automated feedback integration.
- Any professional whose AI agent produces HTML documents that require human review before finalization.
Pricing & Engagement Models
Markloop offers two paid plans with a 14-day free trial and no credit card required. The Solo plan is $19 per month (or $15 per month billed annually) for one creator seat, unlimited projects, documents, versions, and reviewers, plus MCP integration. The Team plan is $49 per month (or $39 per month billed annually) for up to five creator seats, a shared workspace, team roles and permissions, removal of Markloop branding, and priority support. Both plans are offered at a founding price locked in for early users. Custom enterprise options are available by contacting the team.
Why Consider Them
Markloop differentiates itself by being purpose-built for the AI agent review loop. Unlike general-purpose tools like Google Docs or Notion, it preserves the original HTML formatting, anchors comments to specific elements and text quotes, and exports feedback in a machine-readable format that agents can consume directly. The native MCP integration for Claude Code and Codex eliminates manual copy-pasting, and the unlimited reviewer model removes cost barriers for stakeholder feedback. The platform also prioritizes privacy by showing reviewers only the rendered document, not the source file. For teams already using AI coding agents, Markloop offers a streamlined way to incorporate human oversight without breaking the development workflow.
