01-3 weeks of stock left
slow-down SKUs
slow-down SKUs
1-3 weeks of stock left
Case StudyInventoryPrime Day
3 SKUs were days from selling out mid-Prime Day. We caught it in 10 minutes
Claude Code, connected to live Amazon and logistics data through the MCP server, flagged every at-risk and overstocked SKU before Prime Day.
2 weeks free · no credit card
propamp.ai / inventory-risk / prime-day
Agent memo
Prime Day risk map
Traffic-light grid
3 slow7 over2 check
SKU rows
3 SKUs1-3 weeks leftslow-down
7 SKUsoverstockedoverstock
2 SKUszero FR sales for 30 daysinvestigate
16 markets~10-minute memochecked
Agent note: write the PPC adjustments before Prime Day starts.
0
slow-down SKUs with 1-3 weeks left
0
overstocked SKUs to slow down
0
zero-sales FR SKUs to investigate
0 min
agent memo, not a week of review
What the agent found
The risk was not one SKU. It was a mixed inventory map.
Three SKUs were close to stockout, seven were overstocked, and two needed investigation after zero France sales for 30 days.
0capital tied up before Prime Day
overstocked
overstocked
capital tied up before Prime Day
0zero FR sales for 30 days
investigate
investigate
zero FR sales for 30 days
0The whole finding surfaced in a ~10-minute agent memo instead of a manual pre-Prime-Day catalog review.
marketplaces
marketplaces
The whole finding surfaced in a ~10-minute agent memo instead of a manual pre-Prime-Day catalog review.
Traffic-light SKU grid asset
marketplaces
The whole finding surfaced in a ~10-minute agent memo instead of a manual pre-Prime-Day catalog review.
Data on the platform
The agent did not need new data.
Every SCM signal already lived in PROPAMP AI: FBA, AWD, 3PL, supplier, and marketplace-level sales movement.
FBA
sellable stock
AWD
reserve stock
3PL
transferable units
Supplier
incoming coverage
inventory / locations / sku-coverage
Unified inventory view across locations asset
The agent needed to read what was already there.
Best-in-class MCP
Months of data came back in a few requests.
Built for serious data volumes, so the agent reasons over the catalog instead of one SKU at a time.
Few requests. Full context. Minimal token usage.
The MCP connection let Claude Code pull months of Amazon and logistics history in 1-2 minutes, then reason over the whole risk surface.
Months of data
read in a few requests
1-2 minutes
to retrieve the context
Minimal tokens
for serious data volumes
MCP pulling months of data in two requests asset
The agent's read
The memo ended with the next action.
claude-code / inventory-risk-thread
Agent chat panel quote asset
1Ask inventory risk
2Read MCP context
3Draft PPC adjustment
"Some"SomeSKUsSKUsaren'taren'tgoinggoingtotohavehaveenoughenoughstockstockforforPrimePrimeDayDayononcertaincertainmarkets...markets...WantWantmemetotowritewritethethePPCPPCadjustments?"adjustments?"
What changed
The slow-down SKUs did not run out mid-event.
Without the catch, the seller would have lost search rank on the SKUs nearest stockout while leaving overstock capital untouched.
Slow-down SKUs
rank lossstock rebalancedcaught early
Overstock
dead capitalPPC adjusted7 SKUs flagged
No rank loss, no dead overstock capital.
The operator had time to rebalance inventory and adjust advertising before Prime Day demand exposed the risk.
Averted stockout curve versus actual asset
1-3 wks
stock left
~10 min
memo
0
markets
markets
Your move
Start your free PROPAMP AI trial.
Connect your inventory data and let an agent find the stockout and overstock risks before your next peak event.
agent / mcp / inventory-loop
Agent plus MCP plus Seller Central loop asset
AgentMCPInventory