Biarkan AI agent menerima, mengakui, memperbaiki, dan menyelesaikan anotasi halaman web melalui loop feedback kolaboratif secara real-time.
Juga dikenal sebagai thevrus/MarkLayer, marklayer-mcp
- Stars
- 52
- Tools
- —
- Unduhan, 30 hari
- —
- Versi terbaru
- —
- Commit terakhir
- 10 Nov 2026
- Lisensi
- Apache-2.0
Apa itu MarkLayer MCP?
MarkLayer adalah MCP server. Biarkan AI agent menerima, mengakui, memperbaiki, dan menyelesaikan anotasi halaman web melalui loop feedback kolaboratif secara real-time.
Ringkasan dibuat dari README proyek
Tentang MarkLayer MCP server
MarkLayer menyediakan antarmuka kolaboratif untuk feedback web yang dapat berinteraksi langsung dengan AI agent. Pengguna dapat menggambar, menyorot, atau memberikan komentar pada halaman web apa pun yang sedang aktif, termasuk local development server, dan membagikan satu link tunggal kepada kolaborator. Link ini berfungsi sebagai review board real-time di mana manusia dan AI agent bekerja sama melalui antrean anotasi yang terstruktur.
Developer dapat menghubungkan AI agent menggunakan Model Context Protocol melalui remote HTTP transport dengan menambahkan /mcp pada share link, atau dengan menginstal package marklayer-mcp secara lokal via npx. Server ini memungkinkan agent untuk melakukan tindakan spesifik seperti mengakui, memperbaiki, dan menyelesaikan tugas. Tool ini juga menyediakan konteks teknis seperti CSS selector dan computed styles dalam format markdown untuk membantu agent memahami elemen mana yang memerlukan perhatian secara tepat.
Tool ini dirancang untuk QA tester, designer, dan developer yang perlu menjembatani celah antara feedback visual dan perbaikan kode otomatis. Tidak diperlukan akun atau ekstensi bagi reviewer manusia, dan tool ini mendukung pembaruan real-time melalui WebSockets.
Apa yang bisa Anda lakukan dengannya
- 1Automatisasi perbaikan bug UIAI agent dapat memantau daftar anotasi halaman web untuk mengakui, memperbaiki, dan menyelesaikannya secara otomatis.
- 2Melakukan review desain secara real-timeTim dapat menggunakan shared board untuk membuat sketsa ide dan menyorot detail pada situs yang sedang aktif dengan kursor yang terlihat.
- 3Melakukan audit halaman otomatisSeorang agent dapat membaca teks dan kontrol pada sebuah halaman untuk menyarankan pengeditan copy tertentu atau meninggalkan komentarnya sendiri.
Ditulis berdasarkan README proyek. Setiap use case diperiksa terhadap kutipan dari README tersebut.
Cara menginstal MarkLayer MCP
Format diverifikasi 10 Nov 2026Tambahkan ke CursorTambahkan ke GooseInstal MarkLayer MCP di Claude Code
$ claude mcp add marklayer -- npx -y marklayer-mcpInstal MarkLayer MCP di Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"marklayer": {
"command": "npx",
"args": [
"-y",
"marklayer-mcp"
]
}
}
}Instal MarkLayer MCP di VS Code
.vscode/mcp.json
{
"servers": {
"marklayer": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"marklayer-mcp"
]
}
}
}Instal MarkLayer MCP di VS Code CLI
$ code --add-mcp '{"name":"marklayer","type":"stdio","command":"npx","args":["-y","marklayer-mcp"]}'Instal MarkLayer MCP di Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"marklayer": {
"command": "npx",
"args": [
"-y",
"marklayer-mcp"
]
}
}
}Instal MarkLayer MCP di Codex
$ codex mcp add marklayer -- npx -y marklayer-mcpInstal MarkLayer MCP di Codex config.toml
~/.codex/config.toml
[mcp_servers.marklayer] command = "npx" args = ["-y", "marklayer-mcp"]
Instal MarkLayer MCP di Gemini CLI
$ gemini mcp add -s user marklayer npx -- -y marklayer-mcpInstal MarkLayer MCP di Gemini settings.json
~/.gemini/settings.json
{
"mcpServers": {
"marklayer": {
"command": "npx",
"args": [
"-y",
"marklayer-mcp"
]
}
}
}Pengecekan otomatis
Berjalan 13 Nov 2026Laporan lengkap →Lolos checks otomatis kami. Ini bukan audit keamanan: baca kodenya dan berikan server akses paling terbatas yang dibutuhkannya. Cara kerja checks
- Source repository terhubung dan dapat dijangkauLolos
- Lisensi open source (OSI)Lolos
- Ada commit atau release dalam satu tahun terakhirLolos
- Nama package tidak mirip dengan package populerLolos
- Remote endpoint menggunakan HTTPSTidak diperiksa
- Tools yang bersifat destruktif telah diberi labelTidak diperiksa
- Tidak ada instruksi tersembunyi untuk modelLolos
- Tidak ada advisory kritis pada paket atau dependensinyaTidak diperiksa
README
Lihat di GitHubOne URL. A shared board. A faster decision.
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.
- For AI-assisted work: give an agent the share link over MCP and it works the annotations as a live queue: acknowledge, fix, resolve. Nothing to install. Or inspect an element yourself for a stable selector and an AI-ready markdown snapshot.
- For client feedback: let clients point to exactly what they mean, without an account or extension.
- For design review: sketch ideas, highlight details, and keep the conversation attached to the page.
- For QA: pin reproducible issues to the actual UI, then share a clean link with the team.
How it works
- Open a page: paste any public URL at marklayer.app, or use the Chrome extension on the page you are already viewing — including a page on your own
localhostdev server, which never has to be reachable from the internet. - Make the feedback visible: draw, highlight text, measure space, pin a threaded comment, or inspect an element.
- Share one link: collaborators join the same board and see cursors, marks, replies, and calls in real time. Point an AI agent at the same link over MCP instead, and the thread becomes its work queue.
No sign-up. No trial clock. No client install.
What you can do
| 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. |
Built for AI agents
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.
Built to respect the reviewer's time and privacy
- No accounts or tracking: start reviewing immediately.
- Links expire thoughtfully: shared boards expire 90 days after their last view.
- Open source and self-hostable: MarkLayer is released under Apache-2.0, so your workflow is not tied to a pricing change.
Want the non-technical version? Read How MarkLayer works.
Self-hosting & development
git clone https://github.com/thevrus/MarkLayer.git
cd MarkLayer
bun install
bun run dev
For the Chrome extension in development:
- Build or run the extension app.
- Open chrome://extensions/ and turn on Developer mode.
- Choose Load unpacked and select apps/extension/.output/chrome-mv3-dev.
Repository layout
├── 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
Stack
| 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 |
Scripts
| 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 |
Contributing
Found a bug or have an idea? Open an issue. Contributions are welcome.
License
Apache License 2.0 © Dean Rusin
Pertanyaan tentang MarkLayer MCP
Bagaimana cara menambahkan MarkLayer MCP ke Claude Code?
Jalankan claude mcp add marklayer -- npx -y marklayer-mcp di terminal Anda. Tambahkan --scope user agar tersedia di semua proyek.
Bagaimana cara menambahkan MarkLayer MCP ke Cursor?
Buka ~/.cursor/mcp.json dan tambahkan server di bawah mcpServers, menggunakan config Cursor yang ditunjukkan di bagian instalasi di atas.
Apakah saya perlu membuat akun untuk menggunakan MarkLayer?
Tidak, MarkLayer tidak memerlukan pendaftaran atau akun untuk mulai meninjau atau membagikan board.
Bisakah saya menggunakan MarkLayer di local development server saya?
Ya, Anda dapat menggunakan ekstensi Chrome untuk memberikan anotasi pada halaman di server localhost Anda sendiri tanpa perlu dapat diakses dari internet.
Apa yang terjadi dengan board yang saya bagikan seiring berjalannya waktu?
Shared boards tidak bersifat permanen dan akan kedaluwarsa 90 hari setelah terakhir kali dilihat.