Endpoint · extractionPOSThubvibe-io.com /work/data/forecast
Time-series forecasting: forecast any BigQuery table with Google's pretrained TimesFM model (AI.FORECAST), nothing to train.
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Time-series forecasting: forecast any BigQuery table with Google's pretrained TimesFM model (AI.FORECAST), nothing to train. Point it at the table, timestamp column and value column and get forecast rows with bounds for the horizon you set, per series with id_cols. Use it for sales, traffic, demand or metric forecasts. Input: table, timestamp_col, data_col; optional horizon, id_cols.Overview
Grade?
UNRATED
0 of 30 paid calls toward a letter
Price
$10.00 per call
Paid calls
none yet
delivery unknown until someone pays
More info
Seller?
URL
https://hubvibe-io.com/work/data/forecast
MCP server on this host: io.github.Its-fortunatefolly/hubvibe
Seen
first 13 days ago · last 13 hr ago
23 free handshakes
Payment
Pays through
x402 · MPP evm, stripe, tempo
Offered on?
Base USDC, Solana, Tempo USDC.e
Listed on?
Base, Solana
Handshakescomputed 2 days ago
0.741 from 20 free handshakes over 30 days · UNRATED ?
| Component | Weight | Measured | Lower bound ? | Adds | Short ? | Uncertain ? | |
|---|---|---|---|---|---|---|---|
| livenesscosts the most it answered at all |
0.60 | 1.00 | 0.693 | 0.416 | 0 | −0.184 | |
| latency p95 it answered as fast as its class |
0.20 | 0.63 | 0.626 | 0.125 | −0.075 | 0 | |
| price stability the price stayed where it was listed |
0.20 | 1.00 | 1.000 | 0.200 | 0 | 0 | |
| Composite | 1.00 | 0.741 | gap to 1.000 = 0.259 · 0.075 short · 0.184 uncertain | 0.741 | −0.075 | −0.184 |
Not measured: correctness · nobody paid; honesty · nobody paid; schema conformance · no answer had a published shape to check
BURN_INFREE_TIER_ONLY
Verify it yourself
npx teppi-check https://hubvibe-io.com/work/data/forecastcurl -s https://api.teppi.xyz/v1/trust/cap_01M317X6W9W428NDEMAP305W27