Forecast (simple exponential smoothing)
POST /api/forecast-sesSimple exponential smoothing (SES) - level-only forecast for series without trend or seasonality. Send POST /api/forecast-ses with the required fields values and horizon and pay $0.001 per call over x402 or MPP, or call it free by solving a proof-of-work challenge. It returns a JSON object with method, n, horizon, alpha and forecast.
Higher alpha (closer to 1) tracks recent values aggressively; lower alpha (closer to 0) smooths through noise. Default alpha=0.3 is a common conservative pick; pass an explicit alpha or use forecast-eval to pick the one that minimizes backtest error. Forecast is flat (= last fitted level) for all horizons.
Parameters
| Name | Type | Required | Description |
|---|---|---|---|
values | array | yes | Numeric series in chronological order (max 10000, min 3) Also accepted as data, series, numbers, nums, points. |
horizon | number | yes | Number of future periods to forecast (1 to 1000) Also accepted as periods, steps, ahead, forecast. |
alpha | number | no | Smoothing parameter, 0 < alpha < 1 (default 0.3) |
Example request
curl -i -X POST https://agent402.tools/api/forecast-ses \
-H "Content-Type: application/json" \
-d '{"values":[42,44,41,43,45,44,46,45,47,46],"horizon":3,"alpha":0.3}'
Without payment this returns HTTP 402 Payment Required with the exact price for forecast-ses; any x402 v2 or MPP client pays it and retries.
Example response
{
"method": "ses",
"n": 10,
"horizon": 3,
"alpha": 0.3,
"forecast": [
{
"step": 1,
"point": 45.4431,
"lower95": 42.7805,
"upper95": 48.1057
},
{
"step": 2,
"point": 45.4431,
"lower95": 42.6633,
"upper95": 48.2229
},
{
"step": 3,
"point": 45.4431,
"lower95": 42.5508,
"upper95": 48.3354
}
]
}
| Field | Type | Always present | In the example |
|---|---|---|---|
method | string | yes | ses |
n | number | yes | 10 |
horizon | number | yes | 3 |
alpha | number | yes | 0.3 |
forecast | array of objects | yes | 3 items in the example |
From an MCP client
catalog.call {
"slug": "forecast-ses",
"params": {
"values": [
42,
44,
41,
43,
45,
44,
46,
45,
47,
46
],
"horizon": 3,
"alpha": 0.3
}
}
On the hosted connector at https://agent402.tools/mcp, catalog.call runs forecast-ses free (rate-limited, no wallet). Local install: npx -y agent402-mcp.
Errors and behavior
valuesandhorizonare required. An input the tool rejects returns an HTTP 4xx whose body carrieserror,tool,expected,requiredandexample, so the caller can correct it.- A paid call that ends in any status of 400 or above is not charged over x402, MPP or a prepaid credits key: settlement is cancelled when the tool fails. The exception is a Tempo push credential, a transfer the buyer sent before the call: it settles before the tool runs, so if the tool then fails the payment is recorded as a refund owed to the paying wallet.
- Free tier: no outbound network call leaves the server for this tool, so proof-of-work (16 leading zero bits of sha256) pays for it.
- A
GETorHEADto /api/forecast-ses returns the same 402 quote, so the price can be read without a body. - An
Idempotency-Keyheader makes a retried paid call replay the first 200 instead of charging again (an answer larger than 1 MB is not replayed).
Paid call (JavaScript agent)
import { wrapFetchWithPayment } from "@x402/fetch";
import { x402Client } from "@x402/core/client";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";
const client = new x402Client();
client.setSpendControls?.(false); // keep your own spending ceiling in code
registerExactEvmScheme(client, { signer: privateKeyToAccount(KEY) });
const payFetch = wrapFetchWithPayment(fetch, client);
const res = await payFetch("https://agent402.tools/api/forecast-ses", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
"values": [
42,
44,
41,
43,
45,
44,
46,
45,
47,
46
],
"horizon": 3,
"alpha": 0.3
}),
});
No wallet? Pay with compute
Fetch a challenge, solve the sha256 puzzle (16 leading zero bits, a fraction of a second of CPU), and resend with the X-Pow-Solution header:
import { createHash } from "node:crypto";
const lz = (b) => { let t = 0; for (const x of b) { if (!x) { t += 8; continue; } t += Math.clz32(x) - 24; break; } return t; };
const c = await (await fetch("https://agent402.tools/api/pow/challenge?slug=forecast-ses")).json();
let n = 0;
while (lz(createHash("sha256").update(c.challenge + ":" + n).digest()) < c.difficulty) n++;
await fetch("https://agent402.tools/api/forecast-ses", { method: "POST", headers: { "X-Pow-Solution": c.token + ":" + n, "Content-Type": "application/json" }, body: JSON.stringify({"values":[42,44,41,43,45,44,46,45,47,46],"horizon":3,"alpha":0.3}) });
Part of these workflows
Forecast (simple exponential smoothing) is one step in these 2 skill packs, each sold as a single call:
- Trend analysis - Take any numeric time series - a stock's daily close, a FRED macro indicator, a treasury yield history - and run it through the full quantitative workup: descriptives, moving averages, trend line, outliers, optional correlation against a benchmark, and a deterministic forecast forward with a 95% prediction interval. Everything an analyst writes a notebook for, in one chain of cheap calls.
- Forecasting bake-off - Don't guess which forecasting method to trust. Backtest all four (naive/drift, SES, Holt, Holt-Winters) on a real series, rank by out-of-sample RMSE, then forecast forward with the winner and its 95% prediction interval. Method selection without the hand-waving.
Related tools
Forecast (Holt linear trend)
POST /api/forecast-holtHolt's linear trend method - level + trend (no seasonality). Two smoothing parameters: alpha (level) and beta (trend). F…
Forecast (Holt-Winters seasonal)
POST /api/forecast-holt-wintersHolt-Winters triple exponential smoothing - level + trend + seasonal component. Use for series with a repeating cycle (w…
Forecast (naive baselines)
POST /api/forecast-naiveThree textbook baseline forecasts: mean (forecast = average of history), naive (forecast = last value), drift (linear ex…
Crypto price history
GET /api/crypto-historyHistorical price, market cap, and volume time series for a coin. Granularity is automatic per CoinGecko: <=1 day = 5-min…
Forecast backtest (MAPE + RMSE)
POST /api/forecast-evalBacktest a forecasting method on the input series by holding out the last `testSize` observations, forecasting them, and…
Moving average (SMA + EMA)
POST /api/moving-averageCompute simple (SMA) and exponential (EMA) moving averages over a numeric series. Returns one value per input position -…