StationFX Capacity Utilization Total Index 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 the Federal Reserve's monthly capacity utilization rate for total industry (manufacturing, mining, and utilities) with derived trend statistics and inflation-risk thresholds.
Fed measure of output from manufacturing, mining, and utilities as a percentage of capacity. Below 80% signals slack; above 85% signals potential inflation pressure. Use for industrial cycle analysis, capacity investment timing, and inflation risk assessment. Monthly frequency.
Returns an array of monthly observations, each containing the raw capacity utilization rate (%), month-over-month and year-over-year absolute and percentage changes, trailing z-scores (12-month and 5-year), a percentile rank over the trailing 5 years, 3-month and 12-month rolling averages, and an above-trend binary flag. Output is either JSON or compact toon format.
GEThttps://stationfx.com/economic-data/industrial/capacity-utilization-total-index?utm_source=zero.xyzChoose this endpoint when you need the official Federal Reserve capacity utilization series with pre-computed derivative statistics (MoM, YoY, z-scores, percentile ranks, trend flags) in a single call. Prefer it over raw FRED data when you need enriched analytics ready for agent reasoning without additional computation. Ideal for inflation risk monitoring, industrial cycle analysis, or Fed policy context where the 80%/85% threshold semantics matter.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"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": "TCU"
}
}
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