shopify-inventory-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LEAD_TIME_DAYS | No | Optional store-wide lead time in days | 21 |
| SHOPIFY_CLIENT_ID | No | Client ID from your Shopify Dev Dashboard app | |
| SHOPIFY_STORE_DOMAIN | No | Your Shopify store domain, e.g. your-store.myshopify.com | |
| SHOPIFY_CLIENT_SECRET | No | Client secret from your Shopify Dev Dashboard app | |
| SHOPIFY_ADMIN_ACCESS_TOKEN | No | Admin API access token for a legacy admin-created custom app, used instead of client ID/secret |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_at_risk_skusA | List SKUs whose days of cover is at or below lead time (status reorder_now), sorted by urgency. |
| get_sku_forecastB | Daily demand, days of cover, projected stockout date, and status for one SKU. |
| get_reorder_suggestionC | Reorder point and safety stock for a SKU given lead time and service level. |
| explain_forecast_inputsC | Exact history window, formula names, and caveats used for a SKU forecast (auditable). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a clear primary purpose: risk listing, single-SKU forecast, reorder calculation, and audit explanation. The main potential confusion is between get_sku_forecast and get_reorder_suggestion, since both deal with stockout/reorder planning, but their outputs and use cases are sufficiently distinct.
All tool names use a consistent snake_case verb_noun pattern: list_at_risk_skus, get_sku_forecast, get_reorder_suggestion, explain_forecast_inputs. The convention is predictable and easy for an agent to follow.
Four tools is a reasonable, focused set for an inventory forecasting/audit server, with each tool serving a distinct analytical step. It is slightly narrow but not thin enough to be a problem for the stated purpose.
The surface covers core forecasting, reorder recommendation, risk listing, and auditability, but it lacks obvious adjacent operations such as listing all SKUs, retrieving current inventory levels, or updating lead-time/service-level settings. These gaps may force agents to work around missing capabilities.