尚未检测到更新。GitHub 发布版本后会显示在这里。
个人 GitHub 账号下公开仓库的所有者可以登录并验证所有权,自行管理介绍,无需管理员批准。
登录并生成验证文件,在 30 分钟内将其提交到此仓库的默认分支。其他分支或分叉仓库中的文件无效。然后在下方检查文件,即可无需管理员批准直接管理项目。请保留文件以维持管理权限。
如需登录,将前往登录页面。登录后请回到此处,再次点击所选的验证按钮。
在项目文件夹中运行 /nomorevibe verify,即可验证所有权并自行管理介绍。
一分钟完成验证Annotate any webpage with drawings, comments, and highlights. Real-time collaboration for Chrome.
翻译准备中
取自仓库 README
正在加载完整 README。 以下为已保存的摘录。
Website feedback your AI agent can act on.
Draw, highlight, and comment on any live webpage, then share one link. A human reviews it in real time, or an AI agent connects over MCP and works it like a to-do list: acknowledge, fix, resolve, reply.
One URL. A shared board. A faster decision.查看完整 README ↗MarkLayer turns any webpage into a collaborative review surface. Instead of passing screenshots back and forth, send a link. Teammates or clients can open the original page in their own browser, leave feedback where it belongs, and see changes land live. So can an AI agent: each comment arrives with the exact element it refers to already attached.
localhost dev server, which never has to be reachable from the internet.No sign-up. No trial clock. No client install.
| Send an agent to work the page | Every share link is also a remote MCP server, so an AI agent can watch annotations and acknowledge, fix, and resolve them live, or review the page and leave notes of its own. |
| Annotate freely | Pen, highlighter, eraser, shapes, arrows, text, and text-selection highlights. |
| Keep feedback in context | Pin threaded comments to the page, reply inline, and track status. |
| Review live | Real-time cursors, drawings, and comments via WebSocket, plus peer-to-peer voice and video chat. |
| Hand off agent-ready context | Inspect an element for a stable selector, computed styles, parent layout, viewport details, and framework component info, packaged as markdown built for a coding agent's prompt. |
| Measure the UI | Check element dimensions and edge-to-edge gaps between two elements. |
| Share or export | Create shareable links with preview cards, or export annotations to PNG. |
| Make it yours | Reorder toolbar tools; drafts persist locally and restore when you return. |
Every annotation is part of a structured queue: an agent can read it, act on it, and report back, the same way a human would.
Connect over MCP, with nothing installed. Every share link is also a remote MCP server. Add /mcp to it:
claude mcp add --transport http marklayer https://marklayer.app/s/<id>/mcp
Any client that accepts a remote (Streamable HTTP) server URL takes the same address. Add ?agent=cursor, or any name, so the people in the room can see who is doing the work. The share panel on every link shows the command with the id filled in.
If a client only runs local servers, marklayer-mcp has the same tools as a stdio package, installed once for every room:
claude mcp add marklayer -- npx -y marklayer-mcp
Then just ask: "Watch my MarkLayer annotations. For each one, acknowledge it, make the fix, then resolve it with a summary." The agent calls marklayer_watch_annotations in a loop, and the human watches every status change land live. It can go first, too: read_page hands it the page's text and controls with their selectors, so an agent asked to review a page leaves its own comments and suggests exact copy edits as diffs. The full toolset is documented in apps/mcp.
Every mark carries the context an agent needs. Inspecting an element captures its CSS selector, computed styles, parent layout, and framework component info as a markdown snapshot, so a comment arrives with the exact node attached instead of a vague description.
Or from inside the browser. On a browser agent with WebMCP support, the same list, acknowledge, resolve, and reply actions are exposed straight from the page via document.modelContext. Nothing to configure.
Agents can open their own boards, too. The share id is the access token, so minting a room is one unauthenticated POST, handy for seeding a review per URL ahead of time:
curl -X POST https://marklayer.app/api/$ID \
-H 'Content-Type: application/json' \
-d '{"ops":[],"url":"https://example.com","width":1440}'
Discoverable machine-first. /llms.txt, /llms-full.txt, /.well-known/api-catalog, an MCP server card, an agent skill, and a full OpenAPI spec describe the whole surface for an agent that's never seen MarkLayer before.
Want the non-technical version? Read How MarkLayer works.
git clone https://github.com/thevrus/MarkLayer.git
cd MarkLayer
bun install
bun run dev
For the Chrome extension in development:
├── apps/extension/ Chrome extension (WXT + Preact)
├── apps/worker/ Cloudflare Worker, API, real-time rooms, proxy, OG generator
├── apps/site/ Static marketing site (Astro)
├── apps/mcp/ MCP server for AI agents (published as marklayer-mcp)
├── packages/types/ Shared TypeScript types
└── packages/agent-tools/ Agent tool contract shared by the MCP server
| Area | Technologies |
|---|---|
| Frontend | Preact, Signals, Tailwind CSS, Vite |
| Extension | WXT, Chrome APIs |
| Backend | Cloudflare Workers, Hono, Durable Objects |
| Storage | D1 (SQLite), R2 |
| Real-time | WebSockets, WebRTC |
| Agent integration | MCP (remote at every share link, plus a stdio package), WebMCP, OpenAPI |
| Command | What it does |
|---|---|
| bun run dev | Run the workspace in development mode |
| bun run build | Build all apps |
| bun run check | Type-check the workspace |
| bun run lint | Lint and format-check with Biome |
| bun run lint:fix | Apply lint and formatting fixes |
| cd apps/worker && bun run deploy | Deploy the Worker to Cloudflare |
| cd apps/mcp && bun run build | Build the MCP server (marklayer-mcp) to dist/cli.js |
| cd apps/site && bun run indexnow:submit | Ping IndexNow (Bing and friends) after a deploy that changed pages |
Found a bug or have an idea? Open an issue. Contributions are welcome.
Apache License 2.0 © Dean Rusin