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AI e-commerce operations. Inventory, pricing, segmentation, and analytics.
AI e-commerce operations. Inventory, pricing, segmentation, and analytics.
Valid MCP server (2 strong, 3 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. Trust signals: trusted author (4/4 approved).
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Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-enzoemir1-shopops-mcp": {
"args": [
"-y",
"shopops-mcp-server"
],
"command": "npx"
}
}
}From the project's GitHub README.
AI-powered server that implements the Model Context Protocol (MCP) for managing Shopify and WooCommerce stores.
stdio and Streamable HTTP (MCPize).@modelcontextprotocol/sdk v1.29+, Zod v4.# 1. Install the package
npm i shopops-mcp
# 2. Create a .env file (see Configuration section)
cp .env.example .env
# 3. Run the server (local stdio mode)
npx shopops-mcp run --transport stdio
# 4. Or start the HTTP endpoint (MCPize deployment)
npx shopops-mcp run --transport http --port 8080
The server will read the environment variables, connect to the configured store(s), and expose the MCP tools and resources.
| Tool | Description |
|---|---|
store_connect | Connects, lists, disconnects, or syncs a Shopify/WooCommerce store (action: "connect" | "list" | "disconnect" | "sync") and validates credentials. |
store_demo_seed | Creates a realistic demo store (20 products, 40 customers, 150+ orders) so you can explore every tool without real store credentials. |
inventory_status | Returns current stock levels, back-order flags and low-stock alerts. |
inventory_forecast | Projects future inventory requirements using moving-average demand and safety-stock buffers. |
pricing_analyze | Generates a price elasticity report and identifies under-/over-priced SKUs. |
pricing_optimize | Suggests optimal price points based on margin analysis, sales velocity, and configurable pricing rules. |
customers_segment | Performs RFM analysis and assigns customers to one of seven segments. |
customers_churn | Scores customers for churn risk and provides retention recommendations. |
order_anomalies | Detects potentially fraudulent or erroneous orders using pattern-recognition models. |
product_performance | Conducts ABC analysis and returns contribution metrics per product class. |
report_daily | Generates a JSON/CSV daily operations summary (sales, inventory, alerts). |
report_weekly | Generates a weekly performance report with trend visualisations. |
| Resource | Description |
|---|---|
store://overview | High-level store metrics: product, order, and customer counts per connected store. |
store://inventory | Low-stock alerts: active products with on-hand quantity ≤ 10, sorted lowest first. |
store://orders/recent | The 20 most recent orders across all stores, with order number, total, status and date. |
store://customers/top | Top 20 customers by total spending, with name, email and order count. |
ShopOps reads only a handful of environment variables. Store credentials are not env vars —
they are passed to the store_connect tool at runtime (one connection per store), so the same
server process can manage multiple Shopify/WooCommerce stores.
| Variable | Required | Description |
|---|---|---|
PORT | No | If set (or MCPIZE=true), the server runs as a Streamable HTTP endpoint on this port (default 8080) instead of local stdio. |
MCPIZE | No | Set to true by the MCPize runtime to force HTTP transport. |
LEMONSQUEEZY_LICENSE_KEY | No | Pro license key. Without it the server runs in Free tier (see Pro License). |
A minimal .env is provided in .env.example.
Shopify and WooCommerce credentials are supplied as parameters to store_connect, e.g.:
// Shopify
{ "action": "connect", "platform": "shopify",
"store_domain": "myshop.myshopify.com", "access_token": "shpat_..." }
// WooCommerce
{ "action": "connect", "platform": "woocommerce",
"store_url": "https://example.com", "consumer_key": "ck_...", "consumer_secret": "cs_..." }
store_connect returns a store_id that every other tool takes as input. To explore the server
without real credentials, call store_demo_seed instead.
Roadmap (not yet implemented): report anonymization, S3 report export, and a configurable pricing-model / log-level are planned but not read by the current release.
ShopOps ships in Free mode — store_demo_seed, store_connect, inventory_status, pricing_analyze, customers_segment, product_performance, and report_daily are open. The following tools require a Pro license:
inventory_forecast — moving-average demand forecasting + reorder pointspricing_optimize — actionable price-change recommendationscustomers_churn — churn risk scoring + retention recommendationsorder_anomalies — fraud / anomaly detectionreport_weekly — week-over-week trend report + AI insightsBuy a Pro License (€29, lifetime, 3 machines): https://automatiabcn.lemonsqueezy.com/buy/cbbe44f0-a146-4c65-88c8-71f371037758
Or get the Indie MCP Stack Bundle (€69, all 4 servers).
export LEMONSQUEEZY_LICENSE_KEY=YOUR-KEY-HERE
Or in your MCP client config:
{
"mcpServers": {
"shopops-mcp": {
"command": "npx",
"args": ["-y", "shopops-mcp-server"],
"env": { "LEMONSQUEEZY_LICENSE_KEY": "YOUR-KEY-HERE" }
}
}
}
Validation is cached locally for 24 h — fully offline-capable after first run.
ShopOps MCP is released under the MIT License. See LICENSE for full terms.
Author: Automatia BCN
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