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Introduction

recomention answers one question: do AI engines recommend your product? It asks ChatGPT, Claude, Perplexity, Gemini, Grok and Google AI Overview the questions your buyers ask, several times each, and reports how often each engine named you, who it named instead, which sources it read, and what to fix.

The API gives your code and your agents the same thing the website gives a person:

  • Public rankings — who the engines name for a category, with counts. No key needed.
  • Reports — start one for a product, poll it, then read every number and every answer as JSON.
  • The Distribution Kit — a finished report as Markdown files your agent can act on.

Base URL

Section titled “Base URL”
https://api.recomention.com/v1

Every endpoint is under /v1. Requests and responses are JSON over HTTPS. The machine-readable description is the API reference, generated from an OpenAPI 3.1 document.

Where to start

Section titled “Where to start”
  1. Quickstart — create a key and make your first call in two minutes.
  2. Authentication — how keys work and how to keep them safe.
  3. Reports — start, poll, read, and fetch the kit.
  4. MCP server — the same tools inside Claude Code, Cursor or Codex.

Reading the numbers honestly

Section titled “Reading the numbers honestly”

AI engines are not deterministic, so every result is a rate, not a verdict:

  • Quote counts as “named in n of m answers”, never as yes or no.
  • An engine under enginesSkipped did not run — it is never an engine that left you out, and it never counts as zero.
  • An answer with failed: true is in no count. A failed call is not a miss.
  • A report with simulated: true is test data with made-up answers. Draw no conclusions from it.
  • Every report is a dated snapshot. Say the date when you quote it.

Help

Section titled “Help”

recomention.comStatussupport@recomention.com