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StationFX Core CPI (Less Food & Energy)
x402
StationFX Core CPI (Less Food & Energy) is a paid API for AI agents from stationfx.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-02).
Returns U.S. Core CPI (all urban consumers, excluding food and energy) with derived metrics including MoM/YoY changes, z-scores, and percentile ranks for inflation trend analysis.
Price / call$0.005
Success—
StatusUnknown
How this service works
CPI excluding food and energy — the Fed's preferred measure of underlying inflation trend. Strips out volatile components to reveal persistent price pressure. Critical input for Fed policy models and inflation persistence analysis. Monthly frequency with full derived metrics including z-score and percentile rank.
Output
A time-series array of monthly core CPI observations, each containing the raw index value, month-over-month and year-over-year changes (absolute and percent), 12-month and 5-year z-scores, 5-year percentile rank, 3-month and 12-month rolling averages, and an above-trend binary flag.
Example use cases
Fed policy rate decision model
“Get me the last 24 months of core CPI data with YoY percent change and 5-year z-score so I can feed it into our Fed rate decision model — I need to see whether underlying inflation is persistent or fading.”
Macro dashboard inflation widget
“Fetch the most recent core CPI reading along with its month-over-month change, rolling 3-month average, and whether it's above long-run trend — I want to display this on our macro dashboard.”
Historical inflation regime analysis
“I'm doing an inflation regime study — can you grab core CPI monthly data from January 2018 through December 2023, including YoY percent change and the 5-year percentile rank, in compact toon format?”
Technical details
Endpoint
GEThttps://stationfx.com/economic-data/inflation/consumer-price-index-for-all-urban-consumers-all-items-less-food-and-energy-in-u-s-city-average?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need the Fed's preferred core inflation measure — CPI ex-food and energy — with pre-computed derived signals (z-scores, percentile ranks, rolling averages) rather than raw index values alone. Prefer this over headline CPI endpoints when stripping volatile food and energy components is important for analyzing persistent price pressure. Ideal for macro models, Fed policy forecasting, and inflation regime classification where monthly frequency and statistical context are required.
Side effects
- Invalid date format (date_from/date_to not YYYY-MM-DD) returns a 400 error
- Requesting future dates returns empty or partial data
- Unknown field names in the fields parameter may return nulls or errors
- Payment failure via x402 protocol returns 402 with no data
- Very wide date ranges may return large payloads; use field selection to limit
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"schema": {
"type": "object",
"properties": {
"data": {
"type": "array",
"items": {
"type": "object",
"properties": {
"date": {
"type": "string",
"description": "Observation date YYYY-MM-DD"
},
"value": {
"type": "number",
"description": "Raw observed value in series units"
},
"mom_pct": {
"type": "number",
"description": "Month-over-month % change"
},
"yoy_pct": {
"type": "number",
"description": "Year-over-year % change"
},
"zscore_5y": {
"type": "number",
"description": "Z-score relative to trailing 5 years"
},
"mom_change": {
"type": "number",
"description": "Month-over-month absolute change"
},
"yoy_change": {
"type": "number",
"description": "Year-over-year absolute change"
},
"zscore_12m": {
"type": "number",
"description": "Z-score relative to trailing 12 months"
},
"above_trend": {
"type": "integer",
"description": "1 if value is above long-run trend, else 0"
},
"pct_rank_5y": {
"type": "number",
"description": "Percentile rank over trailing 5 years (0-100)"
},
"rolling_3m_avg": {
"type": "number",
"description": "3-month rolling average"
},
"rolling_12m_avg": {
"type": "number",
"description": "12-month rolling average"
},
"trend_direction": {
"type": "integer",
"description": "Trend: 1 rising, -1 falling, 0 flat"
}
}
},
"description": "Observations ordered by date ascending"
},
"meta": {
"type": "object",
"description": "Series metadata: source_key (FRED series ID), units, frequency (D/W/M/Q/A), date_from, date_to, fields"
}
},
"description": "Station f(x) response with metadata and pre-computed derived metrics"
},
"example": {
"data": [
{
"date": "2024-01-01",
"value": 5.33,
"mom_pct": 0,
"yoy_change": 0.5,
"zscore_12m": 1.2,
"trend_direction": 1
}
],
"meta": {
"frequency": "M",
"source_key": "CPILFESL"
}
}
}Tags
x402
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