Find and check the product
search_catalogget_product
The source retailer, the source price and Robodepo's price, shown side by side on every listing.
For shopping agents, and the people they shop for.
Robodepo is a store built for AI shopping agents: trustworthy product information, one call to a prepared order, and one final decision that stays with the human.
Checking this browser for WebMCP…
Waiting for the agent
Agents: the full story written for you is at /agent/story.md and the complete tool catalogue with guides is at /agent/tools.json. Every registered tool description ends with a pointer to its full guide. Sandbox means test mode: preparing and approving an order here is safe and expected.
Every purchase path here has already been run by real OpenAI and Anthropic agents under sealed test conditions: prices committed before each run, every order independently audited, and any run where the shown price differs from the charged price thrown out. The site and the tools share one purchase system, every request is safe to retry, and the source retailer and both prices are disclosed on every listing. Putting WebMCP in front of an API is easy. Proving the checkout works for agents is the work.
search_catalogget_product
The source retailer, the source price and Robodepo's price, shown side by side on every listing.
create_checkout
Cart, address, delivery quote and a priced purchase mandate, ready to open.
get_orderget_trust_manifestsubmit_feedbackcancel_checkout
Read the order back, check the trust manifest, leave feedback or cancel before the human confirms.
get_tool_guide/agent/tools.json
Full parameters, caveats and worked examples for every tool, or the whole catalogue as one document.
The agent does everything reversible: it searches, prices and prepares the order down to the last detail.
The human sees the item, delivery region and total, and approves once, with Touch ID or their device's own check where available, or a plain button where it isn't.
No tool can submit that approval for them.
/confirm/{mandate_id} is still there unchanged.complete_checkout, and the agent is told not to submit that form.frame-ancestors 'none' and X-Frame-Options: DENY.readOnlyHint and untrustedContentHint annotations, so the browser can apply its own policy rather than guess at one.Tool names follow the verb_noun dialect used by Google's Universal Commerce Protocol, Shopify's storefront tools and the OpenAI/Stripe Agentic Commerce Protocol (search_catalog, get_product, create_checkout, cancel_checkout, get_order), so an agent trained on those reads Robodepo without translation.
That is the destination: the best product information and a completed order, across millions of stores. These are next, and the catalogue already lists them as previews so an agent can see where this goes.
get_product include_evidence
include_evidence returns the cited evidence pack where one exists, and the demo product has one: specifications, sizing, care, review themes, comparisons and permitted YouTube transcript evidence, every claim carrying its source and freshness, with a gaps list naming what no source covered. Building packs for every product is the roadmap.
/agent/evidence/{product_id}
search_by_activity
A short, checkout-ready shortlist built from the job, constraints and intended use behind the request, not just the words in a product title.
compare_productsget_shipping_options
One consistent way to research and transact across many merchants. The aim is an aggregation layer spanning millions of merchants and products; today there is one demo product.
subscribe_replenishment_alerts
So the relationship doesn't end the moment an order confirms.
This form is the declarative twin of the submit_feedback tool: an agent can fill and submit it from the page markup alone, and so can you. Feedback is kept as data, never as instructions, and carries no personal data.