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Ecommerce Store Discovery MCP Server

Ecommerce Store Discovery MCP Server

Ecommerce Store Discovery MCP Server

Glama score MCP Registry npm version npm downloads license mcpservers.org

An MCP server for the Mamba Labs Ecommerce Store Discovery actor on Apify. Give it product keywords and a platform. Each run finds stores through Google, confirms each one on its own homepage, and returns one row per store.

What's Inside

Related MCP server: Shop Search MCP

What it does

  • Searches Google with each keyword plus a footprint the platform prints on its stores, and drops marketplaces, social networks, and reference sites.

  • Reads each candidate's robots.txt and homepage, and returns the store only when the homepage carries the platform's marks, with the evidence and a confidence.

  • Per store: payment methods, subscription apps, currencies, Shopify product count, Tranco rank band and trend, contact emails, phone, and Instagram, Facebook, and TikTok links from the homepage.

  • Unconfirmed sites are skipped and not charged.

All of the work runs on Apify. This package is a thin client that starts the actor run, waits for it, and hands back the dataset rows.

Quick start

You need Node.js 18 or newer and an Apify account with an API token.

Add this to your Claude Desktop config (claude_desktop_config.json), Cursor, or any MCP client:

{
  "mcpServers": {
    "mamba-ecommerce-store-discovery": {
      "command": "npx",
      "args": [
        "-y",
        "@mambalabsdev/mcp-ecommerce-store-discovery"
      ],
      "env": {
        "APIFY_TOKEN": "your-apify-token"
      }
    }
  }
}

Restart the client. The discover_ecommerce_stores tool appears.

Prerequisites

Example prompts

  • "Find 30 Shopify stores that sell coffee beans and show their product counts and contact emails."

  • "Which WooCommerce stores in the UK sell dog treats?"

  • "List BigCommerce stores selling auto parts, with their payment providers."

Tool

discover_ecommerce_stores. One tool. Example arguments:

{
  "keywords": ["coffee beans"],
  "platform": "shopify",
  "max_stores": "25"
}

Inputs

Every buyer facing input of the actor, unchanged. Omitted inputs take the actor's own defaults. Numbers and booleans are sent as strings.

Input

Type

Description

keywords

array

What the stores sell. Required

platform

string

shopify (default), woocommerce, bigcommerce, or any

max_stores

string

Confirmed stores to return, up to 500. Default 25

country

string

Google market. Default US

location_term

string

Word added to every search

language

string

Google interface language. Default en

include_product_count

string

true or false. Default true

include_traffic_rank

string

true or false. Default true

include_unconfirmed

string

true or false. Default false

exclude_domains

array

Domains to skip

max_search_pages

string

Cap on Google pages read

max_charge_usd

string

Optional cost cap for the run

Pricing

Pay per event on Apify, billed to your Apify account. Prices in USD.

Event

Free plan

Bronze

Silver

Gold

store-found, one confirmed store

$0.0055

$0.005225

$0.00495

$0.004675

search-page, one Google result page read

$0.019

$0.01805

$0.0171

$0.01615

apify-actor-start, per run start

$0.002

$0.002

$0.002

$0.002

Unconfirmed, refused, and failed sites are free.

Your keys

The actor needs no key. It reads Google result pages through the Apify Google SERP proxy and the stores' own public pages, and holds no key of any kind. Mamba Labs pays the platform and proxy costs of the run.

Full actor documentation

apify.com/mambalabs/ecommerce-store-discovery

License

MIT. See LICENSE.

Available Tools

1 tool
discover_ecommerce_storesDiscover ecommerce storesA
Read-only

Find online stores that sell a product on a given platform (shopify, woocommerce, bigcommerce, or any), with each store confirmed on its own homepage. Give keywords and a platform. One row per store: domain, store_name, platform with platform_confidence and platform_evidence, myshopify_domain, payment_methods, subscription_apps, currencies, product_count (Shopify products feed), Tranco rank band and trend (a rank, not traffic), contact_emails, phone, and Instagram, Facebook, and TikTok links from the homepage, plus the search that found it. Sites that do not show the platform are skipped and not charged. A run that does not succeed is returned as an error with its run ID. Read-only; requires an APIFY_TOKEN; Apify charges per confirmed store and per Google result page read.

Inputs: keywords (required), country, language, platform, +8 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.4/5.0

    Scored across 1 tool

    Disambiguation5/5

    There is only one tool, so there is no possibility of selecting the wrong tool or confusing overlapping purposes. Its purpose is clearly stated as ecommerce store discovery.

    Naming Consistency5/5

    The single tool name follows a clear snake_case verb_noun pattern: discover_ecommerce_stores. Although there is only one name, it is descriptive and internally consistent.

    Tool Count3/5

    A single tool is thin for an MCP server, even one narrowly focused on store discovery. The tool itself is broad and complex, but the surface offers no separate lookup, filtering, or result-management operations.

    Completeness4/5

    The discovery operation returns rich store-level details, platform evidence, contact data, social links, ranking context, and error run IDs. Minor gaps remain, such as no follow-up lookup by domain or pagination/result-management tools, but the core discovery workflow is covered.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data

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