WebLoom MCP server
Commit Oct 29, 2026Drives a local Chrome instance via CDP to perform complex web automation, handle difficult editors, and post to social media platforms.
Also known as webloomhq/engine, engine
- Stars
- 2
- Tools
- 1
- Downloads, 30 days
- —
- Latest version
- 0.3.31
- Last commit
- Oct 29, 2026
- License
- MIT
What is WebLoom MCP?
WebLoom drives a local Chrome instance via CDP to perform complex web automation, handle difficult editors, and post to social media platforms. It exposes 1 tool, such as core.
Summary generated from the project's README
About WebLoom MCP server
Automating complex web interactions through a local Chrome instance is what WebLoom enables for developers using AI clients like Claude Code, Cursor, or Cline. By connecting to a user-opened Chrome browser via the Chrome DevTools Protocol, it allows agents to act as a specific user within their own logged-in sessions. This approach bypasses the limitations of generic automation by using dedicated handlers for difficult editors like Lexical, Draft.js, and Quill, as well as specialized upload strategies.
Users manage different identities through named sessions, each acting as a unique Chrome profile that can utilize its own proxy. The server includes a system called Threads, which stores site-specific knowledge like selectors and quirks to help agents navigate changing web layouts. It provides a wide range of tools for navigation, network capture, and interacting with React internals. Because it runs as a local stdio server, it maintains privacy by default, keeping all page content, cookies, and identity data on the local machine.
What you can do with it
- 1Posting to social media platformsAn agent can post text, images, or videos to X, Reddit, TikTok, or Pinterest even when no open API is available.
- 2Interacting with complex web editorsDevelopers can use specialized setters to input text into sophisticated web components that usually fail with standard automation.
- 3Automating repetitive site tasks with recipesYou can instruct an AI to run a specific sequence of actions on a website using pre-recorded knowledge.
- 4Efficiently reading page contentAn AI client can perform low-cost page scans to get a compact list of elements for interaction.
Written from the project's README. Every use case is checked against a quote from it.
WebLoom MCP tools 1
Detected from the READMEcore
| core | — |
Automated checks
Ran Nov 13, 2026Full report →Not verified yet. A server needs a score of 80, no serious finding, and enough data for us to check. How checks work
- Source repository linked and reachablewebloomhq/engine is public and reachablegithub.com/webloomhq/engine ↗Pass
- Package names this repository as its sourceNot checked
- Build provenance (Sigstore attestation)Not checked
- Open source license (OSI)MITspdx.org/licenses/MIT.html ↗Pass
- Commit or release in the last yearLast commit or release 2026-10-29github.com/webloomhq/engine ↗Pass
- OpenSSF ScorecardNot checked
- Package name not close to a popular packageNot checked
- No critical advisory in the package or its dependenciesNot checked
- No hidden instructions to the model1 tool description and the README read; no override phrases, credential paths or hidden charactersPass
- Destructive tools are labelledNo tool named like delete, drop or execPass
- Remote endpoint answers the MCP handshakeNot checked
README
View on GitHubWebLoom Engine
The browser MCP for agents that have to act as you on hard sites. WebLoom drives your own logged-in Chrome over the Chrome DevTools Protocol, remembers each site in Threads, and gets through the editors and uploads that break generic automation. Open source (MIT), engine for the WebLoom marketplace.
Why WebLoom
- Your sessions, one per account. Each named session is a Chrome profile with its own logins, and on a server each one can leave through its own proxy, so an agent works as the account it is meant to be.
- Threads. Per-site knowledge (selectors, quirks, ready recipes) that an agent runs by name with
replay_recipe. When a site changes, fixing its Thread fixes every agent that uses it. - Hard editors. Setters for Lexical, Draft.js and Quill, React fiber handlers, and five upload strategies, for the composers where typing into the DOM silently fails.
- Posting where there is no open API. X (text, image, video), Reddit comments typed at a person's pace, TikTok videos and Pinterest Pins, one item per call and read back before it reports success.
- Cheap page reads.
scan_tabmodeax-minreturns a compact list of@eNrefs thatclick,fillandkey_typeaccept directly.
Measured against Playwright 1.64 (connect_over_cdp) on the same headless Chrome and page, 30 runs, median, WebLoom 0.3.26:
| Action | WebLoom | Playwright |
|---|---|---|
| Run JavaScript in the page | 4 ms | 4 ms |
| Read the page text | 7 ms | 8 ms |
| Page snapshot with element refs | 7 ms, 4.8K chars | 82 ms, 32K chars |
| Fill a field by name | 6 ms | 27 ms |
| Click by visible text | 261 ms | 51 ms |
The click includes 150 ms of deliberate press and release pacing, so it reads as a person's click on sites that watch for automation.
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. 104 tools become available under the webloom namespace.
Tool profiles
All 104 tools are shown by default. To keep the client's tool list short, set WEBLOOM_TOOLS in the server's env:
| Value | Shown |
|---|---|
core |
28 everyday tools: sessions, tabs, navigate, read, scan_tab, screenshot, click, fill, keys, scroll, wait, upload, eval_js, editor setters, Threads and recipes |
core,posting |
core plus X, Reddit, TikTok and Pinterest posting |
core,network |
core plus network capture, request replay and websockets |
core,marketplace |
core plus browsing, installing and publishing Threads |
| any tool name | added on top, e.g. core,solve_captcha |
Hidden tools stay callable, so scripts and recipes that use them keep working.
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 statusany 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>/latestevery 6h to pull free Thread patches. Disable viaWEBLOOM_AUTO_UPDATE=off. Engine binary itself does NOT auto-update. - Playbook: local only. Never transmitted. Lives at
~/.webloom/playbook.json. You cancatit. - 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
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_fileStrategies A to 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 to $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 dev@webloom.run.
Author + contact
Built by MarStudio. Primary contact: dev@webloom.run.
Issues and PRs welcome. Open one at https://github.com/webloomhq/engine/issues.
WebLoom MCP questions
What tools does WebLoom MCP provide?
It exposes 1 tool, including core.
Does WebLoom run its own browser?
No, it drives a real Chrome instance that the user explicitly opens via the Chrome DevTools Protocol (CDP) debug port.
Is my data sent to WebLoom servers?
By default, it sends zero data, including no analytics, telemetry, or calls home. Telemetry is off by default and must be explicitly enabled.
How does WebLoom handle complex web editors?
It includes specialized setters for Lexical, Draft.js, and Quill, as well as React fiber handlers to manage editors where standard DOM typing fails.
Can it post to social media platforms?
Yes, it can post text, images, and videos to platforms like X, Reddit, TikTok, and Pinterest even where no open API exists.