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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.

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
propamp.ai / inventory-risk / prime-day
Inventory risk dashboard showing stockout signals, marketplace coverage, and Prime Day SKU readiness across purchase orders

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.

slow-down SKUs

0

1-3 weeks of stock left

overstocked

0

capital tied up before Prime Day

investigate

0

zero FR sales for 30 days

marketplaces

0

The whole finding surfaced in a ~10-minute agent memo instead of a manual pre-Prime-Day catalog review.

Sankey diagram showing purchase order PO 190 flowing from suppliers through fulfillment IDs to US, Germany, Canada, and UK marketplaces

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
Ad adjustment recommendations for Prime Day prep showing slow-down, diagnostic, and push actions across US, UK, CA, DE, and FR marketplaces

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 workflow showing months of Amazon and logistics data retrieved in minutes with minimal token usage

The agent's read

The memo ended with the next action.

Agent inventory risk thread showing Prime Day stock warnings and PPC adjustment recommendations

Agent memo

Some SKUs aren't going to have enough stock for Prime Day on certain markets... Want me to write the PPC adjustments?

  1. 1Ask inventory risk
  2. 2Read MCP context
  3. 3Draft PPC adjustment

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

stock rebalanced

Was rank loss

caught early

Overstock

PPC adjusted

Was dead capital

7 SKUs flagged

Outcome proof

1-3 wks

stock left

~10 min

memo

0markets

markets

No rank loss, no dead overstock capital.

The operator had time to rebalance inventory and adjust advertising before Prime Day demand exposed the risk.

First-hand

BRANDCUBE

Startup Amazon seller

3 SKUs caught · ~10 minutes

Three SKUs were days from selling out mid-Prime Day while seven others were overstocked. Propamp’s agent surfaced the whole risk map in about ten minutes — before we lost rank or tied up more cash.

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 / seller-central loop
Propamp.ai MCP server connected to Claude for supply planning
AgentMCPSeller Central