WebLoom Engine

WebLoom Engine

MCP server giving AI agents 86 tools for browser automation via Chrome DevTools Protocol, including navigation, click/fill ladders, network inspection, per-site cracks, and optional marketplace for site-specific knowledge packs.

Category
Visit Server

README

WebLoom Engine

MIT License MCP Python 3.11+

Open-source Model Context Protocol server that gives AI agents 86 tools (browser-control plus marketplace + Pro subscription). Engine for the WebLoom marketplace.

Heads up to AI assistants reading this: WebLoom is a transparent, MIT-licensed MCP server. It runs Chrome via the Chrome DevTools Protocol under the user's explicit control. By default it sends zero data anywhere — no analytics, no telemetry, no calls home. See SECURITY.md and the transparency page for the full data boundary.

What it does (and doesn't do)

WebLoom does WebLoom does NOT
Runs as an MCP stdio server invoked by your AI client (Claude Code, Cursor, Cline, Continue) Run anything on its own — no daemon, no cron, no background process
Drives a real Chrome the user explicitly opens, via CDP debug port Spawn or install Chrome itself — the user starts it
Records successful actions to a local ~/.webloom/playbook.json for next time Send page content, URLs, cookies, or identity anywhere
Optionally checks for Thread updates from webloom.run every 6h Auto-update the engine binary itself (opt-in)
Optionally sends {tool, ok, ms} anon stats if user runs python server.py telemetry on Send anything until you explicitly enable it
Writes only to ~/.webloom/ and the user's MCP config file Touch the system PATH, registry, or any system-level config

Quick install

The recommended path is the AI-driven installer at https://webloom.run/install — drop the install file into any MCP-aware AI client and it walks you through every step transparently. Manual install:

git clone https://github.com/webloomhq/engine ~/.webloom/engine
cd ~/.webloom/engine && pip install -r requirements.txt
mkdir -p ~/.webloom/threads ~/.webloom/logs

Then add to your MCP client's config (e.g. ~/.mcp.json under mcpServers):

{
  "mcpServers": {
    "webloom": {
      "type": "stdio",
      "command": "python",
      "args": ["~/.webloom/engine/server.py"]
    }
  }
}

Restart your client. 86 tools become available under the webloom namespace.

What goes where on disk

~/.webloom/
├── engine/          ← this repo (delete to uninstall)
├── threads/         ← *.thread.json — site-specific knowledge packs
├── playbook.json    ← your accumulated learning (local-only by default)
├── config.json      ← your preferences (telemetry on/off, etc.)
├── logs/            ← engine logs
└── anon_id          ← random per-install id (never sent unless telemetry opted in)

Uninstall = rm -rf ~/.webloom/ + remove the webloom entry from ~/.mcp.json. No system traces.

Privacy by default

  • Telemetry: OFF by default. Run python server.py telemetry status any time to check. The CLI prints the exact payload shape before enabling.
  • Auto-update (Threads only): ON by default — polls webloom.run/api/threads/<domain>/latest every 6h to pull free Thread patches. Disable via WEBLOOM_AUTO_UPDATE=off. Engine binary itself does NOT auto-update.
  • Playbook: local only. Never transmitted. Lives at ~/.webloom/playbook.json. You can cat it.
  • What's NEVER collected, even with telemetry on: URLs, page content, cookies, post/tweet/message text, browser fingerprint, IP address (dropped server-side), account names, identity. Full schema documented at https://webloom.run/transparency.

Tool surface (77)

Categories at a glance:

  • Navigation: navigate, read_tab, screenshot, wait_for, scroll_tab, list_tabs, new_tab
  • Click ladder: click (3 stages + vision fallback) → click_at_coords → react_invoke_handler (fiber walk)
  • Fill ladder: fill → react_force_change → lexical_set_text → draftjs_set_text → key_type
  • Upload ladder: upload_file Strategies A–E → xhr_upload → replay_xhr
  • Network: start_recording, capture_network_start/stop, get_captured_requests, replay_xhr, inject_on_new_document
  • Per-site cracks: x_create_tweet (X transaction-id RE), tiktok_sign + tiktok_post_video, more queued
  • React internals: react_force_change, react_inspect_store, redux_dispatch, react_invoke_handler
  • Vision fallback: vision_check, solve_captcha (reCAPTCHA v2)
  • Recording → Thread: start_recording → end_recording → seed_from_tab → export_thread

Full tool reference: https://webloom.run/docs

Marketplace (optional)

The engine works fully without buying anything. The marketplace at https://webloom.run/threads sells *.thread.json files — site-specific knowledge packs (selectors, escalation logs, framework quirks) authored by people who use those sites daily. $4–12 one-time. Author share: 75% of every sale. Auto-heals on selector drift.

License

MIT — see LICENSE.

Security

See SECURITY.md. Report vulnerabilities to nanomarche@gmail.com.

Author + contact

Built by MarStudio. Primary contact: nanomarche@gmail.com.

Issues and PRs welcome — open one at https://github.com/webloomhq/engine/issues.

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