gg402 · Grocery List Optimizer
Generate optimized grocery lists with cost-saving substitutions, meal suggestions, and budget-conscious planning based on dietary constraints.
What it does
Generate optimized grocery lists with cost-saving substitutions, meal suggestions, and budget-conscious planning based on dietary constraints.
- Reduce grocery costs by 15-30% through strategic substitutions
- Generate weekly meal plans that minimize food waste
- Adapt recipes for dietary restrictions while maintaining budget targets
Ideal buyer
Meal planning apps and budget-conscious consumer platforms needing AI-powered grocery optimization.
Run this through your governed agent wallet.
- 01Bootstrap AXON once with
npx @axon402/init. - 02Use the AXON runtime MCP tools to
search_x402_servicesorinspect_x402_offerfor this service. - 03Quote, test-buy, then run the governed paid fetch through AXON.
Send this
Prompt for your agent
A natural-language instruction for your LLM agent — with this endpoint exposed as a tool — to call this resource. Not sent to the endpoint; the endpoint consumes the JSON body below.
Pasting this prompt into a raw ChatGPT or unconfigured agent will notexecute the paid endpoint flow. Run it through an agent with the AXON runtime / MCP tools exposed (see “Use with AXON” above) so the 402 challenge, quote, and governed fetch are handled for you.
“Optimize this grocery list for a family of four on a $150 weekly budget: chicken breast, salmon, quinoa, organic vegetables, almond milk.”
Endpoint request body
The JSON payload your agent sends to the endpoint.
Advanced HTTP details
For integrators who need the raw protocol surface. Most agents should use AXON above instead of calling these directly.
Endpoint URL
curl fallback
curl https://gg402.vercel.app/grocery_list_optimizer \ -H "Content-Type: application/json" \ -H "X-PAYMENT: [signed_payment_envelope]"
Payment & settlement details
Raw on-chain settlement parameters. AXON above handles these automatically through quote / test-buy / governed fetch.
Price & network
Trust & risk
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