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StationFX M2 Money Supply
x402
StationFX M2 Money Supply 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. M2 money supply time series data with derived metrics including MoM/YoY changes, z-scores, trend flags, and rolling averages, going back to 1959.
Price / call$0.005
Success—
StatusUnknown
How this service works
Broad U.S. money supply including cash, checking, savings, and money market accounts. Monitored for inflation signals and monetary transmission analysis. Rapid M2 growth preceded the 2021-2023 inflation surge. Monthly frequency with full derived metrics and history back to 1959.
Output
Returns a JSON array of monthly M2 money supply observations, each including the raw value in series units, month-over-month and year-over-year absolute and percent changes, 12-month and 5-year trailing z-scores, a 5-year percentile rank, a binary above-trend flag, and 3-month and 12-month rolling averages. History available from 1959 to present.
Example use cases
Inflation signal monitoring dashboard
“Get me the latest U.S. M2 money supply readings for the past 24 months, including month-over-month and year-over-year changes, so I can flag whether rapid monetary expansion is signaling a new inflation risk.”
Historical monetary policy research
“I need M2 money supply data from January 2000 to December 2023 with the 5-year z-score and above-trend flag included — I'm studying how money supply behavior correlates with past inflation cycles.”
Macro regime classification for quant strategy
“Fetch the most recent 12 months of M2 money supply data with rolling 3-month and 12-month averages and the percentile rank over the trailing 5 years — I want to classify the current monetary regime as expansionary or contractionary for my asset allocation model.”
Technical details
Endpoint
GEThttps://stationfx.com/economic-data/money-supply/m2?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need U.S. M2 money supply data with pre-computed derived metrics (z-scores, YoY, MoM, trend flags, rolling averages) in a single call rather than fetching raw series and computing derivatives yourself. Prefer it over FRED direct access when you want agent-friendly formatting (toon mode) or need normalized comparison metrics already calculated. Ideal for inflation monitoring, monetary policy analysis, and macro regime detection use cases.
Side effects
- Invalid date format returns an error — dates must be YYYY-MM-DD
- Requesting future dates beyond the most recent monthly release returns no data or an empty array
- Unsupported fmt value (not 'json' or 'toon') may cause a 400 error
- Payment failure via x402 protocol results in a 402 Payment Required response
- Requesting fields that don't exist in the schema may return null values or be silently ignored
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": "M2SL"
}
}
}Tags
x402
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