New llms.txt, docs your coding agent can read →

The API behind every unit you sell

One REST API for inventory, orders, shipping and analytics across Shopify, Amazon, bol.com, Kaufland and more. Signed webhooks, a single-binary CLI, and a reference built for humans and agents alike.

first request
$ curl https://api.stockpilot.dev/inventory?page_size=1 \
    -H "X-CLIENT-ID: $SP_CLIENT_ID" \
    -H "X-CLIENT-SECRET: $SP_CLIENT_SECRET"

{
  "count": 1284,
  "results": [{
    "sku": "TSHIRT-BLK-M",
    "quantity": 42,
    "offered_stock": 38,
    "location": "A1-001-01"
  }]
}

Agent-ready

Documentation your coding agent can actually read

ReDoc is for you. llms.txt is for the model in your editor. Both are generated from the same OpenAPI schema on every request, so neither can drift.

  • llms.txt is a compact index of all 74 operations, grouped by tag.
  • llms-full.txt adds every operation with parameters, request bodies and real response examples.
  • openapi.json is the raw schema, for generating a typed client in any language.
  • SKILL.md ships with the CLI so Claude, Cursor and Codex know how to drive it.
in your editor
# point any agent at the whole API
> Read https://api.stockpilot.dev/llms.txt
> then list every SKU that runs out
> within two weeks.

Reading llms.txt … 74 operations
GET /inventory?page_size=1000
GET /analytics/items/sales

7 SKUs below two weeks of cover:
  TSHIRT-BLK-M   42 units · 9d
  MUG-WHT-330    18 units · 4d

Surface area

One API, the whole operation

Everything a multichannel seller runs on, built from the same objects the Stockpilot app itself uses.

Ready when you are

Your first request takes five minutes

Generate a key in Settings → API, call /auth/who-is, and you are in.

Two developers reading through Stockpilot API code on a laptop