E-Commerce Intelligence MCP Server
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Shopify store analysis, product catalog extraction, pricing strategy, and inventory monitoring
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- Web Scraping, Other
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🛒 E-commerce Intelligence MCP Server — Shopify Store Analyzer for Claude / ChatGPT
Connect AI agents to Shopify store data through the Model Context Protocol (MCP). Clean JSON tuned for LLM function-calling. Pay-per-use, no subscription.
This MCP server exposes2 Shopify toolsto your AI agent:
- analyze_shopify_store— analyze a Shopify store (store-level overview)
- get_store_products— retrieve a Shopify store's product catalog
All responses are structured JSON for LLM tool use. This server coversShopify stores only.
- Shopify research agents— pull a store's product catalog into an analysis
- Competitive research on Shopify merchants— review a Shopify store's public catalog
- E-commerce chatbots— answer questions about a Shopify store's products
Wire this MCP server into an MCP-compatible client (Claude Desktop, Cursor, Windsurf, Cline) by pointing your config at this actor's MCP endpoint:
https://nexgendata--ecommerce-intelligence-mcp-server.apify.actor/mcp
This actor uses Apifypay-per-eventpricing — charged per successful tool call, no monthly subscription.
Q: Does it cover Amazon or other marketplaces?No. This server covers Shopify stores only.
Q: Does it do price comparison, price tracking, or price history?No. It analyzes a Shopify store and lists its products at the time of the call. There is no price-history or price-tracking feature.
Q: Does it monitor SKU/inventory levels or competitor inventory over time?No. There is no inventory-monitoring or competitor-inventory feature.
Q: Can the AI agent call this from Cursor / Cline / Claude Desktop?Yes — any MCP-compatible client works.
NexGenData publishes a catalog of Apify actors and a family of MCP servers for AI agent workflows. Browse the full catalog at](https://docs.apify.com/llms-full.txt)https://apify.com/nexgendata
- Web Scraping MCP Server— general web scraping for AI agents
- Social Content MCP Server— social content data for AI agents
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '<YOUR_API_TOKEN>' with your token const client = new ApifyClient({ token: '<YOUR_API_TOKEN>', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/ecommerce-intelligence-mcp-server").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '<YOUR_API_TOKEN>' with your token. client = ApifyClient("<YOUR_API_TOKEN>") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("nexgendata/ecommerce-intelligence-mcp-server").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
echo '{}' | apify call nexgendata/ecommerce-intelligence-mcp-server --silent --output-dataset
{ "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgendata/ecommerce-intelligence-mcp-server" } } }
The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send anAuthorization: Bearer <APIFY_API_TOKEN>header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).
Download the OpenAPI definition:https://api.apify.com/v2/actors/9Rjliaasiet0JaC0k/builds/t6nkOLFH1Taub1Z2E/openapi.json
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