Norce Backend MCP Servers — End-to-End Use Cases

This page shows what you can do with the Norce Backend MCP Servers when they are connected to an AI assistant. For setup and connection instructions, see Using the Norce Backend MCP Servers.

Each use case below describes what the AI coordinates across servers and includes a sample prompt you can use or adapt.

Importing a supplier catalogue

A complete supplier import typically involves three domains in parallel:

1. Product MCP — import product content: names, descriptions, category assignments, parametric values, and flags.
2. Pricing MCP — import list prices into the relevant client price list.
3. Supplier MCP — import supplier cost prices and register the products against the supplier record.

The AI reads the import data, determines what goes where, and coordinates the three servers — submitting the product import first, then running the price and cost imports in parallel, and polling all three jobs until they complete.

"Import this supplier catalogue. It contains product content, retail prices, and supplier costs. Handle all three and let me know when it's done."

Validating a configuration before go-live

Before an environment goes live, the Config MCP can pull a complete overview of applications, stores, sales areas, VAT codes, and price list assignments. The Pricing MCP can run a health check on each active price list. Together they produce a structured readiness report in a single conversation.

"Give me a configuration overview of Acme Stage and flag anything that looks incomplete or misconfigured."

Investigating a pricing or availability issue

When a product is displaying incorrectly, the AI can query the Pricing MCP, Inventory MCP, and Product MCP in parallel and combine the results — what previously required three separate API calls and manual correlation becomes a single question.

"Product AB-1042 is showing incorrectly in the store. Check the price, the stock availability, and the product status all at once."

Checking products before publication

Before products go live, the Product MCP can check a set of SKUs against readiness requirements and return a clear list of what is missing — translations, required parametric values, active status flags, and broken references.

"Check these 12 SKUs and tell me what's missing before they can go live."

Scheduling operational changes in advance

AI assistants that support scheduling can prepare and execute timed operations — campaign activations, price updates, flag changes — without anyone needing to be at a keyboard when they run. A typical workflow prepares all the data in advance, schedules the activation, and has the AI validate and report the result when it runs.

"Schedule the Summer Campaign flag update for Monday at 06:00. When it runs, validate that all the campaign products are active and correctly priced, then post a summary to the #campaigns Slack channel."

This kind of workflow combines the Backend MCP Servers with scheduling and notification tools. The AI handles the full sequence — preparation, activation, validation, and reporting — automatically.