ShopOps MCP

AI-powered server that implements the Model Context Protocol (MCP) for managing Shopify and WooCommerce stores.

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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.

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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.

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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.

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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.

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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 (default 30).

Optional variables:

Variable	Description
MCP_ENABLE_ANONYMIZATION	When set to true, personally identifiable data is masked in reports.
MCP_REPORT_S3_BUCKET	If provided, daily/weekly reports are uploaded to the specified S3 bucket.

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License

ShopOps MCP is released under the MIT License. See LICENSE for full terms.

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Author: Automatia BCN