Trending tokens
Tokens with the highest momentum over the requested window. The score compares the current window to the prior equal-length window, so a token that suddenly accelerates ranks above a steady high-volume token. Brand-new mints with no prior-window activity get a fast-riser boost. Pass include_score=true to expose the per-component formula_breakdown so you can re-sort client-side.
Rug filter: tokens whose price collapsed by 90% or more inside the window are excluded by default — their activity is rug-watchers piling in, not organic demand. Set include_rugged=true to opt in.
Pagination: use offset + limit to page through the scored list. The response carries total (how many candidates were scored before slicing), offset, and limit so you can detect end-of-list. Pricing/liquidity are USD via the Pyth SOL/USD oracle.
Authorizations
Preferred for swaps-api endpoints (/swaps/*, /stats/*, /trending, /pool-events).
Query Parameters
Trend window.
1m, 5m, 15m, 1h, 4h, 6h, 24h Page size — number of results to return.
1 <= x <= 200Page offset — skip the first N scored results. Combined with limit for stable-cache-window pagination.
0 <= x <= 200Restrict to one sector tag (e.g. meme, defi).
Add trending_score and formula_breakdown to each result.
Include tokens whose price dropped by 90% or more inside the window. Default false.
Comma-separated list (max 3) of additional windows to populate change_pct_by_window on each result (e.g. 5m,24h). Each extra window is one parallel ClickHouse query, so don't ask for more than you'll use.
Response
Trending list

