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PopNx MCPMCP servers for people who use AI · explained in plain words

webEmbedding

by jongko54version 0.3.13i★ 14iComputer or cloud
Registry nameio.github.jongko54/web-embedding

How to install

What it does

Clone any web page from a URL into a verified offline HTML copy, embed, or rebuild.

  • Connects Computer or cloud
  • Account or key No key needed
  • Category Web & browsers

Install

Pick the AI app you use, then copy the settings.

Passed 5/5 checks · What you ask goes through the maker’s server (webembedding-jongkos-mcp.vercel.app) · ✓ Commands checked Nov 13, 2026

First: which AI do you use?

Pick your app and the steps appear below.

Works with Claude · about 2 min

No key, nothing to install · Set it up once on claude.ai or the desktop app, then use it in chat · free accounts can add 1 · on Team/Enterprise an Owner adds it

  1. Open Claude’s Connectors page

    CustomizeConnectors

    CustomizeConnectors1Add2https://…3Add4
  2. Click “Add” → “Custom” → “Web” and fill in these 2 fields

    Copy each value into the field with the same name in Claude, then click Continue

    Name · NamewebEmbedding
    Remote MCP server URL · Addresshttps://webembedding-jongkos-mcp.vercel.app/mcp

    Click Continue past the sign-in settings Claude detected · under Authentication choose what the maker says (Sign in now, Sign in when needed or No sign in), then click Add

  3. Turn it on in a chat

    +ConnectorswebEmbedding

  4. Try it

    Use webEmbedding and tell me what you can do for me, then show me one thing

    ✓ If Claude says it is using webEmbedding or shows a webEmbedding tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with ChatGPT, depending on your plan

Full MCP: ChatGPT Business, Enterprise or Edu on the web · Pro: connects with read/fetch permissions, so tools that change data may not work · Plus: not confirmed in OpenAI’s docs; if you see an add-custom-MCP option on the Plugins page you can try these steps · web only

  1. Open ChatGPT’s add-MCP page on the web

    Plugins+Add custom MCP server

    ChatGPTPlugins1+2https://…3Create4
  2. Fill in the name and address

    Enter a name, paste the address under Connection, tick the risk warning and click Create as a plugin

    Name · NamewebEmbedding
    Connection · Addresshttps://webembedding-jongkos-mcp.vercel.app/mcp
  3. Pick webEmbedding in a chat

    Start a new chat and pick webEmbedding from your plugins before typing

  4. Try it

    Use webEmbedding and tell me what you can do for me, then show me one thing

    ✓ If ChatGPT says it is using webEmbedding or shows a webEmbedding tool in the answer, you are connected

Menu names checked against OpenAI’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Claude Code · about 2 min

No key, nothing to install

  1. Open Terminal

    Mac: press Command+Space and type Terminal · Windows: open PowerShell

  2. Paste this command and press Enter

    claude mcp add --transport http --scope user web-embedding https://webembedding-jongkos-mcp.vercel.app/mcp
  3. Type /mcp in Claude Code

    You should see webEmbedding listed as connected

  4. Try it

    Use webEmbedding and tell me what you can do for me, then show me one thing

    ✓ If Claude Code says it is using webEmbedding or shows a webEmbedding tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Cursor · about 2 min

No key, nothing to install

  1. Click this button to open Cursor

    Open in Cursor

    Cursor asks you to confirm; click Install

  2. Open the AI chat in Cursor in Agent mode

  3. Try it

    Use webEmbedding and tell me what you can do for me, then show me one thing

    ✓ If Cursor says it is using webEmbedding or shows a webEmbedding tool in the answer, you are connected

Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with VS Code · about 2 min

No key, nothing to install

  1. Click this button to open VS Code

    Open in VS Code

    VS Code asks you to confirm; click Install

  2. Open the AI chat in VS Code in Agent mode

  3. Try it

    Use webEmbedding and tell me what you can do for me, then show me one thing

    ✓ If VS Code says it is using webEmbedding or shows a webEmbedding tool in the answer, you are connected

Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.

See every app that uses MCP →

Address for apps that connect over the web

Addresshttps://webembedding-jongkos-mcp.vercel.app/mcp

JSON settings are under “For developers” below

Stuck? Ask people who use webEmbedding💬 Discussion →
For developers: Terminal commands and JSON settings

Over the web

Claude Code

claude mcp add --transport http --scope user web-embedding https://webembedding-jongkos-mcp.vercel.app/mcp

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "web-embedding": {
      "url": "https://webembedding-jongkos-mcp.vercel.app/mcp"
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "web-embedding": {
      "type": "http",
      "url": "https://webembedding-jongkos-mcp.vercel.app/mcp"
    }
  }
}

Installed on your computer

Claude Code

claude mcp add --scope user web-embedding -- npx -y web-embedding mcp

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "web-embedding": {
      "command": "npx",
      "args": [
        "-y",
        "web-embedding",
        "mcp"
      ]
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "web-embedding": {
      "command": "npx",
      "args": [
        "-y",
        "web-embedding",
        "mcp"
      ]
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "web-embedding": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "web-embedding",
        "mcp"
      ]
    }
  }
}

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

At a glance

Downloads per weeki
157/wk
Connection
Computer or cloud
Transport
stdio, streamable-http
Latest versioni
0.3.13
Published to registryi
Nov 8, 2026
Code last changedi
Nov 8, 2026
Maker
jongko54
Packages
npm: web-embedding
Website
github.com
Registry status
Active

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Connect over the internet in

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

Run on your computer in

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

All apps, with pros and cons →

Related guides

What it can do

Tool names and descriptions exactly as the server reported them on Nov 15, 2026. The maker wrote them, not us; we show them as plain text.

  • detect_runtime_capabilities

    Report hosted Apps SDK readiness, read-only runtime capabilities, unsupported capture behavior, and the local stdio command.

  • inspect_url

    Fetch a public or user-authorized URL and inspect title, metadata, frame policy, and likely source/embed candidates. Does not capture screenshots or persist artifacts.

  • discover_embed_candidates

    Extract likely embed, preview, viewer, remix, and source URLs from a public or user-authorized page.

  • classify_clone_mode

    Decide whether a reference should be embedded, sourced, locally captured, bounded-rebuilt, or blocked before reproduction.

  • generate_embed_snippet

    Generate an iframe snippet for a known frameable and authorized URL. Does not verify frameability by itself.

  • plan_reproduction_path

    Create a source-first plan that separates exact embed/source reuse from local capture and bounded rebuild work.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 15, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account jongko54, which owns the repo

  • ✓ Pass

    Still maintained

    Code last changed 7 days ago

  • ✓ Pass

    Has a licence

    Uses MIT

  • ✓ Pass

    Endpoint responds

    Responded in 581 ms (HTTP 200)

  • – Not applicable

    Sign-in with OAuth

    No sign-in needed

  • ✓ Pass

    No hidden instructions in tool descriptions

    Read 6 tool descriptions and found no hidden instructions to the AI

Published vulnerabilities (OSV.dev)

No entries on OSV.dev for web-embedding@0.3.13

Checks only this package version, not every dependency · checked Nov 15, 2026

What we check → · JSON

Makers: ask for a re-check or report wrong info

Discussion

Ask, share a tip or report that it does not work. Sorted by what people marked helpful.

No posts yet. Be the first to ask or share.

Posts here are written by users, not the PopNx team.

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User reviews

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Compared with others in Web & browsersi

  • More stars than 93% of the other 1526 servers in this category
  • Published to the registry more recently than 83% of the other 1526 servers in this category
  • Basic checks equal to or better than 100% of the other 1526 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is webEmbedding safe?

It passed 5 of 5 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed 7 days ago, and the latest version (0.3.13) reached the registry 7 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT on the web (full MCP on Business and above; Pro read-only).

What can I use instead?

In the same category: Browser Use, changedetection.io (official), Apify MCP Server, Actionbook, Flowershow

Similar alternatives

Same category, other makers, commands already checked. Official ones first, then by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Browser Use

Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.

by browser-useWidely used↓ 1.7M/wk★ 121KUpdated 25 days ago

Computer or cloud✓ service owner · browser-use.com

changedetection.io (official)

Official changedetection.io MCP: web page change tracking, back-in-stock and price alerts.

by dgtlmoonWidely used★ 35.8KUpdated 10 days ago

Runs in the cloud✓ service owner · changedetection.io

Apify MCP Server

Extract data from any website with thousands of scrapers, crawlers, and automations on Apify Store ⚡

by apifyWidely used★ 16.3KUpdated 2 days ago

Runs in the cloud✓ service owner · apify.com

Actionbook

Let your AI agent operate any website through a real, logged-in browser session.

by actionbookGrowing★ 1.6KUpdated 27 days ago

Runs in the cloud✓ service owner · actionbook.app

Flowershow

Publish Markdown and HTML from your AI session as a live website. No account needed.

by flowershowGrowing★ 1.1KUpdated 20 days ago

Runs in the cloud✓ service owner · flowershow.app
  • Browser Use — Cloud or install on your computer · Needs a key · In Claude’s directory
  • changedetection.io (official) — Runs in the cloud, nothing to install · No key needed
  • Apify MCP Server — Runs in the cloud, nothing to install · Needs a key
  • Actionbook — Runs in the cloud, nothing to install · No key needed
  • Flowershow — Runs in the cloud, nothing to install · No key needed

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

webEmbedding

webEmbedding clones any web page from its URL for AI coding agents. Give Claude Code, Codex, Cursor, or any MCP client a URL and it returns a verified clone: the original embed when the page allows it, otherwise a self-contained offline HTML snapshot (inlined CSS, shadow DOM, localized fonts and images) or a bounded rebuild, scored against desktop, tablet, and mobile screenshots of the live page.

Add it to your agent in one line:

claude mcp add web-embedding -- npx -y web-embedding@latest mcp   # Claude Code

codex mcp add web-embedding -- npx -y web-embedding@latest mcp # Codex CLI

Then ask: *"Clone https://example.com into ./clone and tell me the fidelity score."* (Machine-readable summary for LLMs: llms.txt.)

webEmbedding is a source-first website cloning engine: it captures live pages with Playwright, replays network evidence from HAR artifacts, rebuilds only when direct reuse is blocked, and self-verifies the result.

It ships as a Skill + MCP server. Instead of asking a model to "clone this site" from a screenshot, it inspects the URL, chooses a reuse or rebuild route, captures DOM/runtime HTML/styles/assets/network traces, generates bounded frontend reconstruction artifacts, and checks the output with visual, DOM, computed-style, interaction, and responsive-breakpoint verification.

GitHub listing, social preview, and launch-copy recommendations are in docs/github-listing.md.

Current Status

The current pipeline is strongest for static and semi-static web pages:

  • company, brand, marketing, and documentation pages
  • public landing pages
  • iframe-blocked pages that need capture-based reconstruction
  • responsive page snapshots across desktop, tablet, and mobile

It is not a full backend or app-logic clone engine. Login-only screens, app-first or native-app-required services, captcha-heavy sites, maps, games, canvas/WebGL-heavy pages, real-time feeds, payments, booking flows, and private server behavior still need separate handling.

Operationally, the repo is now a production-candidate clone engine for URL-based capture and bounded reconstruction: jobs can be queued, network evidence can be replay-audited from HAR artifacts, authenticated dashboard runs can be driven from user-owned browser state, and local gates verify the route corpus, score checks, package contents, and CI wiring. The remaining hard boundary is server-side product behavior, not front-end evidence capture and reconstruction.

Measured Checkpoints

Local benchmark runs from this repo (scripts/check_clone_quality_bench.py, mobile + tablet breakpoints, 2026-10-28):

URLPathScoreWall time
https://developer.mozilla.org/en-US/runtime snapshotroot 99, visual 100, mobile 99, tablet 99~34 s
https://lit.dev/ (web components / shadow DOM)runtime snapshotroot 99, visual 100, mobile 98, tablet 98~40 s
https://www.mozilla.org/runtime snapshotroot 95, visual 100, mobile 95, tablet 95~43 s (was ~160 s)
https://www.python.orgruntime snapshotroot 98, visual 100, mobile 98, tablet 94~226 s (was ~1011 s, failed at 73)
https://www.example.comexact reuseready yes—

These are generated by the local self-verify pipeline, not manually assigned ratings. Earlier bounded-rebuild previews embedded the reference screenshot, which inflated their visual score; the runtime snapshot renders real DOM and CSS, and every row above was also checked by side-by-side screenshot review. Known gap: layouts that page scripts compute for viewports other than the captured one (for example masonry footers) can still drift at tablet width. The reproducible commands and score thresholds are tracked in docs/benchmark-evidence.json. Production readiness gates are tracked in docs/production-pipeline-gates.json.

Core Features

  • Source-first routing:
  • direct iframe or embed reuse when it is safe and frameable
  • original preview, export, remix, or source routes when available
  • bounded rebuild only when exact reuse is unavailable
  • Live browser capture:
  • DOM snapshot
  • runtime HTML
  • full-page screenshot
  • computed style summaries
  • CSS analysis
  • asset inventory
  • HAR-like network metadata
  • interaction states and replay traces
  • storage state export for session-aware flows
  • Blocked-site rebuild:
  • handles X-Frame-Options and CSP-blocked pages by rebuilding from captured evidence
  • generates reusable frontend reconstruction artifacts from captured page structure
  • preserves custom tags, shadow-root host structure, and semantic document structure where captured
  • Evidence limitation reporting:
  • separates directly captured artifacts from inferred or missing evidence in reproduction results and prompts
  • marks app-gated, auth-gated, and native-app-led surfaces as bounded evidence, with recommendations for user screenshots or authenticated session capture
  • Operational failure classification:
  • reports typed pipeline action codes such as network-replay-limited, auth-session-missing, public-app-gate, and canvas-visual-fallback
  • exposes HAR/network replay_readiness before treating captured network evidence as replay-grade
  • Production pipeline helpers:
  • filesystem-backed async clone job queue with durable JSON records, worker locks, retry scheduling, cancellation, and manifest annotation
  • deterministic HAR replay engine for standard HAR, near-HAR, and captured network/manifest.json artifacts
  • authenticated dashboard live corpus runner that accepts user-provided storage_state_path or user_data_dir outside the repo
  • Self-verification:
  • screenshot similarity
  • DOM snapshot similarity
  • computed-style similarity
  • hover/focus/click interaction state parity
  • interaction trace parity
  • desktop/mobile/tablet breakpoint reports
  • Responsive benchmark support:
  • primary desktop viewport: 1440x1200
  • tablet profile: 768x1024
  • mobile profile: 390x844
  • Repair loop:
  • bounded self-repair can run when the first scaffold misses the readiness threshold

Install

Requirements
  • Node.js 18 or newer
  • Python 3.9 or newer
  • Chrome or Chromium available locally for Playwright runtime capture

The package uses playwright-core; it does not download a browser by itself.

Installing this project adds the source-first-clone plugin bundle, the exact-clone-intake skill, and the MCP server that exposes the URL inspection, capture, rebuild, and verification tools.

Install From npm
npm install -g web-embedding

web-embedding install web-embedding doctor

Clone a public URL after installing:

web-embedding clone \

--url https://developer.mozilla.org/en-US/ \ --output-dir ./.tmp/mdn-clone \ --wait-seconds 2 \ --timeout-seconds 35 \ --breakpoints mobile tablet

If you already have an older local plugin installed, overwrite it with:

web-embedding install --force

web-embedding doctor

You can also run the installer without a global install:

npx web-embedding install
Use As An MCP Server

For MCP clients that can launch npm stdio servers:

{

"mcpServers": { "source-first-clone": { "command": "npx", "args": ["-y", "web-embedding@latest", "mcp"] } } }

For local smoke testing:

npx web-embedding@latest mcp

The MCP Registry identity is io.github.jongko54/web-embedding; server.json and package.json#mcpName are kept in sync for registry ownership verification.

Hosted Apps SDK Intake Endpoint

The public remote MCP intake endpoint for Apps SDK Developer Mode is:

https://webembedding-jongkos-mcp.vercel.app/mcp

It exposes low-risk source-first routing tools such as URL inspection, embed candidate discovery, clone-mode classification, and embed snippet generation. Full browser capture, HAR replay, queues, bounded rebuilds, and one-pass clone execution remain local-first through the stdio MCP package.

Apps SDK review pages are hosted alongside the endpoint: https://webembedding-jongkos-mcp.vercel.app/privacy.html, https://webembedding-jongkos-mcp.vercel.app/terms.html, and https://webembedding-jongkos-mcp.vercel.app/submission.html.

Sandboxing And Approvals

webEmbedding has two different execution boundaries:

  • Hosted Apps SDK intake: read-only URL routing and classification only. It accepts absolute http and https URLs, does not run Playwright, does not read local files, does not use browser profiles or storage state, and does not persist capture artifacts.
  • Local stdio MCP and CLI: full capture, HAR replay, queues, rebuild scaffolds, and self-verify run on the user's machine under the user's local agent and filesystem permissions. Output is written only to caller-provided paths such as output_dir or queue_root.
  • Authenticated capture: session-aware runs require the caller to intentionally provide a storage_state_path or user_data_dir. webEmbedding does not collect credentials, perform login bypasses, or treat a public login shell as private app evidence.
  • Access-controlled surfaces: paywalls, captcha flows, private dashboards, payment/checkout/account/admin flows, and native-app-led screens should be blocked, marked needs_session, or sent to manual review unless the user has explicit authorization and supplies the needed evidence.

Local URL entrypoints reject non-HTTP schemes such as file:// so an agent cannot use clone/capture tools as a local file reader. Telemetry is disabled by default and, when enabled, excludes target URLs, local paths, captured HTML, screenshots, storage state, environment variables, API keys, and command output.

Agent Marketplaces

This repository includes marketplace metadata for the two local agent surfaces:

  • Codex: .agents/plugins/marketplace.json points to ./bundle/source-first-clone.
  • Claude Code: .claude-plugin/marketplace.json points to the same bundle and the bundle includes .claude-plugin/plugin.json.

Claude Code users can add the marketplace from GitHub with:

/plugin marketplace add jongko54/webEmbedding

/plugin install source-first-clone@webembedding

AI auto-selection expectations and golden prompts live in docs/ai-distribution.md and evals/ai-selection/webembedding-golden-prompts.json.

Install From Release
curl -fsSL https://github.com/jongko54/webEmbedding/releases/latest/download/install.sh | bash
Install From This Checkout
git clone https://github.com/jongko54/webEmbedding.git

cd webEmbedding npm install node ./bin/web-embedding.mjs install node ./bin/web-embedding.mjs doctor

Install Into A Temporary Home

Useful for testing without touching your real agent home:

python3 python/web_embedding/installer.py install --target-home ./.tmp/home

python3 python/web_embedding/installer.py doctor --target-home ./.tmp/home python3 python/web_embedding/installer.py uninstall --target-home ./.tmp/home

Opt-in Telemetry

Telemetry is disabled by default. On an interactive first install, web-embedding install asks once and defaults to No. Non-interactive installs such as CI and curl | bash do not prompt. If you opt in, web-embedding sends a small anonymous command-completion event to a JSON POST endpoint you control. It does not send target URLs, local paths, captured HTML, screenshots, storage state, environment variables, API keys, or command output.

Enable it during install:

web-embedding install --telemetry --telemetry-endpoint https://your-collector.example/events

Or manage it later:

web-embedding telemetry enable --endpoint https://your-collector.example/events

web-embeddin

Only the beginning is shown; read the rest in the repo