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Prelaunch Radar MCP Server

Developer ToolsLow Risk10.0MCP RegistryRemote
Free

Server data from the Official MCP Registry

Phishing/typosquat domains imitating a brand, from CT logs. Weekly email: $2.99/mo on Gumroad.

About

Phishing/typosquat domains imitating a brand, from CT logs. Weekly email: $2.99/mo on Gumroad.

Remote endpoints: streamable-http: https://mcp.apify.com/?tools=prelaunch-radar/brand-lookalike-watch

Security Report

10.0
Low Risk10.0Low Risk

Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

Endpoint verified · Requires authentication · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "io-github-yzf75011-ui-brand-lookalike-watch": {
      "url": "https://mcp.apify.com/?tools=prelaunch-radar/brand-lookalike-watch"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

New Shopify Stores — MCP tool for AI agents

Give your agent a live feed of new Shopify stores, including pre-launch ones (still behind their password page), plus a Shopify checker for any list of domains. One flat JSON object per store, pay per result, no personal data.

The tool runs on Apify and is served by the official Apify MCP server, so any MCP client (Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, n8n, LangChain, CrewAI) can use it.

Want the full raw database directly? Download the fresh snapshot (1,300+ stores) for $4.99 — one CSV, no subscription, no agent needed.

Also in this repo: Brand Lookalike Watch — phishing and typosquatting domains imitating a brand, from the same CT logs, as an MCP tool.

Connect in one paste

Remote (recommended, sign in with Apify in the browser): add this to your client's MCP config

{
  "mcpServers": {
    "new-shopify-stores": {
      "url": "https://mcp.apify.com/?tools=prelaunch-radar/new-shopify-stores-pre-launch-radar"
    }
  }
}

Local (stdio, with an Apify API token): see clients/local-stdio.json.

Claude Code: claude mcp add --transport http new-shopify-stores "https://mcp.apify.com/?tools=prelaunch-radar/new-shopify-stores-pre-launch-radar"

What the agent can ask

  • "List today's new Shopify stores in the US that are still pre-launch." → {"mode": "feed", "sinceDays": 1, "status": "pre-launch", "countries": ["US"]}
  • "Which of these domains run on Shopify, and when were they registered?" → {"mode": "enrich", "domains": ["example.com"]}
  • maxItems caps billed results, so spend is bounded before the call.

Fields: store_domain, store_name, status (live | pre-launch), niche, country, region, currency, products, collections, ships_to, product_types, sample_titles, domain_registered (RDAP), first_detected.

Automate it: new stores into Clay, n8n, Make or your CRM

No server to run. Import integrations/n8n/new-shopify-stores-daily.json into n8n (Workflows → Import from file):

  1. Every morning at 8 triggers the workflow.
  2. Set your settings holds everything you change: webhookUrl, sinceDays (1), status (any, pre-launch or live), countries (e.g. US, GB, empty = all) and maxItems (100), which caps what one run can bill.
  3. Get new Shopify stores (Apify) calls the Actor. Add a Header Auth credential: name Authorization, value Bearer <your Apify API token>.
  4. Keep store fields keeps domain, name, status, niche, country, currency, products and dates.
  5. Send each store to your webhook posts one JSON object per store to any URL: a Clay table webhook, a Make custom webhook, Slack, HubSpot, your own endpoint.

Lead scoring version: ranked stores into Google Sheets and Slack

integrations/n8n/new-shopify-stores-lead-scoring.json goes further: it skips stores already seen in earlier runs, scores each new store from 0 to 10 (pre-launch, your target niches and countries, small catalog, ships abroad, young domain) with the reasons written out, logs every store in Google Sheets (updated by domain), sends one Slack alert per hot store and one digest for the warm ones. Sample data is pinned, so a first test run needs no Apify token.

A niches filter can be added to the Apify request body. The feed holds business-level public data only; any contact enrichment you add downstream is your own processing, under your own compliance.

Links

How it works

Public Certificate Transparency logs (RFC 6962) → public DNS records pointing to Shopify → official RDAP registry → each store's public /meta.json and /products.json.

LEGAL DISCLAIMER

This dataset is provided for market research, trend analysis, and competitive intelligence purposes only, on an "as-is" and "as-available" basis without warranties of any kind. Records originate exclusively from publicly accessible sources (Certificate Transparency logs, public DNS and RDAP registries, and stores' public storefront metadata); no personally identifiable information (PII) is collected or sold. Independently developed, not affiliated with, authorized, or endorsed by Shopify Inc. or Apify. By accessing this data, you agree that the provider shall not be liable for any direct or indirect damages resulting from its use; in any event, liability is limited to the purchase price.

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