Getting started
The Buyary Evidence Layer.
Synthesized product intelligence for AI agents, over Buyary’s published catalog.
When an agent is asked “should I buy this?”, the open web gives it marketing pages, affiliate listicles, and review spam. Buyary gives it the synthesis: a composite Buyary Score with expert/user/value sub-scores, verified claims, and per-source consensus — every field traceable to independent sources, with raw reviews and store listings deliberately omitted.
The whole surface is two tools, callable over remote MCP or plain REST: get_product_intelligence for one product, and get_product_intelligence_batch for up to five at once. Issue a key once — it works on both protocols — point your client at the service, and your agent answers buying questions from the Evidence Layer instead of guessing. When nothing confidently matches, it says so rather than returning a wrong product.
Where to go next
Key → connected → first call in under five minutes, over MCP or REST.
Authentication & keys →The bearer model: one-time key reveal, revocation, and 401 semantics.
MCP →The agent-native transport: server URL, per-client config, tool discovery.
REST API →The same service over plain HTTP: two endpoints, same keys, byte-identical responses.
get_product_intelligence →The tool’s argument, both response shapes, and resolution semantics.
get_Up to 5 products in one call: results in input order, honest rate accounting.
Data model →Field-by-field tables for every response object, verbatim from the backend.
Errors & limits →Auth errors, the limited-coverage contract, and key lifecycle semantics.
Changelog →What shipped on the Buyary API and this portal, by date.