Skip to main content
Glama

Smart DOM MCP Server

Token-efficient browser automation for AI agents. Drop-in alternative to Playwright MCP that filters the DOM before returning it — only interactive elements, grouped by page section.

Why?

Playwright MCP sends the full accessibility tree on every interaction. On complex pages, that's 10-40K tokens per snapshot. Your 128K context fills up after ~3-12 actions.

Smart DOM filters to only interactive elements (buttons, links, inputs, selects, dialogs) and caps output at 30 elements per section with dedup. Result: 3-13x fewer tokens.

Site

Playwright MCP

Smart DOM

Reduction

Amazon

~37K tokens

~3.2K tokens

11x

Hacker News

~10K tokens

~757 tokens

13x

GitHub

~10K tokens

~2.5K tokens

4x

Wikipedia

~8.4K tokens

~2.6K tokens

3.3x

Actions in 128K context window:

  • Amazon: 3 (Playwright) → 39 (Smart DOM)

  • Hacker News: 12 → 169

Related MCP server: Better Playwright MCP

Install

git clone https://github.com/Frontrunner0x/smart-dom-mcp.git
cd smart-dom-mcp
npm install
npx playwright install chromium

Setup

Claude Code

claude mcp add smart-dom -s user -- node /path/to/smart-dom-mcp/src/index.js

Claude Desktop / Cursor / etc.

Add to your MCP config:

{
  "mcpServers": {
    "smart-dom": {
      "command": "node",
      "args": ["/path/to/smart-dom-mcp/src/index.js"]
    }
  }
}

Tools

navigate

Open a URL and get filtered interactive elements grouped by page section.

navigate({ url: "https://github.com" })
→ { sections: { header: [...], main: [...] }, totalShown: 90 }

dom_summary

Re-scan current page for interactive elements. Use focus to get only one section.

dom_summary({ focus: "main" })
→ { section: "main", elements: [...], count: 28 }

dom_act

Click, type, select, check/uncheck elements by their ref (from navigate/dom_summary).

dom_act({ ref: "@e5", action: "click" })
→ { ok: true, action: "clicked", label: "Sign in" }

dom_act({ ref: "@e12", action: "type", value: "hello world" })
→ { ok: true, action: "typed", value: "hello world" }

dom_read

Extract readable content: tables, headings, alerts, form values, or plain text.

dom_read({ selector: "main" })
→ { headings: [...], tables: [...], text: "..." }

screenshot

Visual fallback. Capture viewport, full page, or a specific element.

screenshot({ fullPage: true })
screenshot({ selector: "#results" })

wait

Wait for text to appear, disappear, or a fixed delay.

wait({ text: "Results loaded" })
wait({ seconds: 2 })

How it works

  1. Persistent Chromium session — browser stays open across tool calls (no cold start per action)

  2. DOM filterquerySelectorAll for interactive elements only, grouped by ARIA landmarks (header, nav, main, sidebar, footer, dialog)

  3. Dedup + cap — identical label+role combos are deduplicated, max 30 elements per section

  4. Ref system — each element gets a stable ref (@e0, @e1, ...) for use with dom_act

  5. Playwright actionsdom_act uses Playwright's native click/fill/selectOption for reliability with SPAs

Limitations

  • Headless only — no access to your logged-in browser sessions (use Chrome DevTools MCP for that)

  • No iframe support — elements inside iframes are not captured (planned)

  • No shadow DOM — web components with shadow roots are not traversed (planned)

  • Single tab — one page at a time

License

MIT

F
license - not found
-
quality - not tested
D
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Frontrunner0x/smart-dom-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server