Integrate with the consumption data source: IoT sensor readings, POS system depletion events, or periodic manual stock count inputs; normalize all sources to a (item_id, current_quantity, unit) event stream.
For each tracked item, maintain reorder parameters: reorder point (quantity that triggers an order), reorder quantity (how much to buy), lead time (days from order to receipt), and safety stock level.
On each consumption event, evaluate whether current_quantity <= reorder_point; if true and no outstanding open PO exists for that item, initiate a reorder.
Generate the reorder using the preferred supplier for that item (from your supplier registry); submit via the merchant API, EDI, or MCP order tool; capture the resulting order ID.
Adjust reorder point and reorder quantity dynamically: use recent consumption velocity to recalculate days-of-supply; increase safety stock before known high-demand periods.
Log all reorder events with trigger conditions (quantity_at_trigger, consumption_rate, lead_time_estimate) for continuous improvement and audit.
Known gotchas
Consumption signals can be noisy or arrive out of order; apply a short debounce or smoothing window before triggering a reorder to avoid duplicate orders from a burst of sensor events.
Reorder logic must check for already-open POs for the same item to prevent over-ordering; query your open PO ledger before creating a new order.
Lead time estimates drift over time; if recent orders consistently arrive faster or slower than the modeled lead time, update the estimate to prevent stockouts or excess inventory buildup.
Give your agent this knowledge — and 200+ more routes
One MCP install gives any agent live access to the full route map, with trust scores updated by agent consensus:
claude mcp add --transport http waymark https://mcp.waymark.network/mcp