ShopOps MCP
AI-powered server that implements the Model Context Protocol (MCP) for managing Shopify and WooCommerce stores.
Features
- Store connectors for Shopify and WooCommerce.
- 11 MCP tools covering inventory, pricing, customers, orders, product performance and reporting.
- 4 MCP resources exposing store overview, inventory, recent orders and top customers.
- Inventory forecasting using moving-average demand plus safety-stock calculation.
- RFM-based customer segmentation (7 distinct segments).
- Data-driven pricing analysis with margin-based optimization suggestions.
- Order anomaly / fraud detection.
- ABC analysis of product performance.
- Automated daily and weekly reports.
- Dual transport: local
stdio and Streamable HTTP (MCPize).
- TypeScript,
@modelcontextprotocol/sdk v1.29+, Zod v4.
- Free tier, plus $25 and $45 paid plans.
Quick Start
# 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.
MCP Tools
| Tool | Description |
|------|-------------|
| store_connect | Establishes a connection to a Shopify or WooCommerce store and validates 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. |
MCP Resources
| Resource | Description |
|----------|-------------|
| store://overview | High-level store metrics: total sales, orders, customers, and gross margin. |
| store://inventory | Full inventory catalogue with quantity on hand, reserved stock and forecasted shortages. |
| store://orders/recent | List of the most recent 100 orders with status, total value and payment method. |
| store://customers/top | Top 50 customers ranked by lifetime value, purchase frequency and recency. |
Configuration
Create a .env file at the project root. The following variables are required:
| Variable | Required for | Description |
|----------|--------------|-------------|
| SHOPIFY_API_KEY | Shopify | Private app API key. |
| SHOPIFY_API_PASSWORD | Shopify | Private app password. |
| SHOPIFY_STORE_DOMAIN | Shopify | Store domain (e.g., myshop.myshopify.com). |
| WOOCOMMERCE_CONSUMER_KEY | WooCommerce | REST API consumer key. |
| WOOCOMMERCE_CONSUMER_SECRET | WooCommerce | REST API consumer secret. |
| WOOCOMMERCE_STORE_URL | WooCommerce | Store URL (e.g., https://example.com). |
| MCP_PORT | HTTP transport | Port for the Streamable HTTP endpoint (default 8080). |
| MCP_LOG_LEVEL | All | Logging verbosity (error, warn, info, debug). |
| MCP_PRICING_MODEL | Pricing tools | Pricing strategy (margin_based). |
| MCP_FORECAST_WINDOW_DAYS | Inventory forecast | Number of days to forecast (
... View full README on GitHub
