question in, a natural-language answer
back. Each is backed by the same assistant a merchant reaches from the dashboard, so
an agent asking through MCP gets the same answer a person would get asking in the
product.
Both are gated by scope like every other tool here: a connection that lacks the
scopes below never sees the tool in tools/list, rather than seeing it and having the
call fail.
optimize_ask
Answers questions about this store’s A/B tests and profit-optimization program: how running experiments are performing, which variant is winning, profit-per-visitor, and what to test next. Scopes required:read_experiments and read_products
string
required
The natural-language question for the Optimize assistant.
read_products is granted so the assistant can name the products under test; it
does not on its own unlock margin data. Profit-per-visitor is backed by
store_cost_model, kept separate from the catalogue grant because it carries
per-variant cost, not just price.sales_ask
Answers sales and shopper-experience questions for this store using the Mercemur sales assistant: product questions, catalog guidance, and order lookups. Scopes required:read_orders and read_products
string
required
The natural-language question for the Sales assistant.
read_orders is required because the assistant’s own tools look orders up. A
connection scoped to the catalogue alone can ask product questions but not order
questions, matching what it could do calling the REST API directly.