Verified official statistics, one API.

Two calls to see the whole idea

# 1. The latest US unemployment rate, with provenance on every value:
curl "https://starwell.dev/api/starwell/v1/sources/fred/series/UNRATE/observations?latest=3"

# 2. A computed, cited answer:
curl -X POST "https://starwell.dev/api/starwell/v1/answer" \
  -H "Content-Type: application/json" \
  -d '{"question": "What was the average US unemployment rate in 2024?"}'

Base URL: https://starwell.dev/api/starwell/v1. All responses use { success, data, meta } envelopes. Dates are ISO YYYY-MM-DD. Machine-readable spec: OpenAPI 3.1.

Anonymous preview now, API keys for volume

No key is required during the preview: anonymous callers get 120 data requests per minute and 6 answers per 10 minutes, per IP.

API keys (Authorization: Bearer dlk_live_... or X-API-Key) lift you onto daily tier quotas with usage metering. Free keys are issued instantly at /keys (or POST /v1/keys with {"email": "..."}); the key is shown once and stored hashed.

Read the store

GET/v1/sources

The sources served, with counts, cadence notes, and terms links.

GET/v1/catalog

The whole catalog flat, in one call: every served series with its indicator, unit, frequency, geography, coverage, verification status, license, and dataset context. The right first call for bulk consumers and agents that want the full universe without walking sources one by one. Parameters: q (ranked search across series ids, indicators, geographies, and dataset titles, e.g. ?q=unemployment+canada), source (restrict to one slug), limit (1..1000; defaults to 50 with q, else all). A human-browsable view lives at /catalog.

GET/v1/sources/:source/datasets

Datasets (official releases and tables) in one source, with coverage and links to the official table pages.

GET/v1/sources/:source/datasets/:datasetId

One dataset plus its series, each with its verification status. The envelope carries the citation block.

GET/v1/sources/:source/series/:seriesId

Full series metadata, current verification status, and the most recent golden and freshness check records.

GET/v1/sources/:source/series/:seriesId/observations

The values. Parameters: start, end, latest (1..5000), limit, offset, format (json or csv; the CSV variant is spreadsheet-ready and carries its attribution as leading # comment lines). Series are addressed by the ids practitioners already use: fred/UNRATE, statcan/v41690973.

{
  "success": true,
  "data": [
    {
      "period": "2026-06-01",
      "value": 4.2,
      "status": "normal",
      "revision": 1,
      "provenance": {
        "sourceUrl": "https://api.stlouisfed.org/fred/series/observations?series_id=UNRATE&...&api_key=REDACTED",
        "retrievedAt": "2026-07-04T13:38:34.644+00:00",
        "connectorVersion": "1.0.0"
      }
    }
  ],
  "meta": {
    "series": { "externalId": "UNRATE", "indicator": "Unemployment Rate", "unit": "Percent" },
    "verification": { "status": "passing", "lastVerifiedAt": "2026-07-04T13:41:05..." },
    "citation": {
      "source": "Federal Reserve Economic Data (FRED)",
      "dataset": "Employment Situation",
      "url": "https://fred.stlouisfed.org/release?rid=50"
    }
  }
}

GET/v1/sources/:source/series/:seriesId/stats

Summary statistics computed over the verified store: latest and previous values, all-time min and max, mean, and the change versus the previous period and versus a year ago. The cheap way to answer "what is it now and how has it moved" without a full analysis run. The envelope carries verification, license, and citation like every other endpoint.

POST/v1/answer

Ask a question in plain language. The engine matches it to served series (or use series to pin them), materializes the verified observations, writes and executes real Python in a sandbox, and returns the computed result. Nothing in the numbers is model-estimated.

curl -X POST "https://starwell.dev/api/starwell/v1/answer" \
  -H "Content-Type: application/json" \
  -d '{
    "question": "What was the average US unemployment rate in 2024?",
    "series": [{ "source": "fred", "seriesId": "UNRATE" }],
    "start": "2024-01-01", "end": "2024-12-01"
  }'

{
  "success": true,
  "data": {
    "answer": "The average US unemployment rate in 2024 was 4.03%.",
    "chart": { "...": "Plotly figure JSON" },
    "python": "import pandas as pd\ndf = pd.DataFrame(data)\n...",
    "series": [{
      "source": "fred", "seriesId": "UNRATE",
      "verification": { "status": "passing", "lastVerifiedAt": "..." },
      "citation": { "dataset": "Employment Situation", "url": "https://fred.stlouisfed.org/release?rid=50" }
    }]
  },
  "meta": { "observationsUsed": 12, "cached": false, "durationMs": 12085 }
}

Expect 10 to 40 seconds on a cache miss; repeated questions are served from the answers cache in milliseconds and invalidated the moment the underlying official data moves. When no served series can answer, the API refuses honestly with a 422 instead of inventing a number.

POST/v1/monitors

Watch a series; get a webhook the moment it moves. Body: {"source": "fred", "seriesId": "DGS10", "webhookUrl": "https://..."}. Requires an API key (keys are free). Detection rides the store's own refresh loop: when a refresh lands a new period or a revised value, Starwell POSTs a series.updated event with the new value, the previous period, the verification status, and the citation. Delivery is https-only, one attempt per refresh, and the monitor's snapshot only advances on successful delivery, so a missed delivery re-fires on the next refresh. Manage with GET /v1/monitors and DELETE /v1/monitors/:id (scoped to your key). Monitors per key: 5 free, 100 pro.

{
  "event": "series.updated",
  "source": "fred",
  "seriesId": "DGS10",
  "indicator": "Market Yield on U.S. Treasury Securities at 10-Year Constant Maturity",
  "period": "2026-07-10", "value": 4.21, "previousPeriod": "2026-07-09",
  "verification": "passing",
  "citation": { "dataset": "H.15 Selected Interest Rates", "url": "https://fred.stlouisfed.org/release?rid=53" }
}

Verification statuses

MCP server

The same capabilities as native tools for any MCP client, served over Streamable HTTP with no session state:

https://starwell.dev/api/starwell/mcp

Tools: search_catalog, list_sources, list_datasets, get_series, get_observations, answer, and monitor management (create_monitor, list_monitors, delete_monitor — API key required). Example client configuration:

{
  "mcpServers": {
    "official-statistics": {
      "type": "http",
      "url": "https://starwell.dev/api/starwell/mcp"
    }
  }
}

Three ways in, thirty seconds each

Python and pandas

The CSV endpoint reads straight into a DataFrame; the # attribution lines are skipped with comment.

import pandas as pd

df = pd.read_csv(
    "https://starwell.dev/api/starwell/v1/sources/fred/series/UNRATE/observations?format=csv",
    comment="#", parse_dates=["period"],
)
print(df.tail())

JavaScript

const r = await fetch(
  "https://starwell.dev/api/starwell/v1/sources/fred/series/UNRATE/stats"
);
const { data, meta } = await r.json();
console.log(data.latest, meta.citation.text);

Google Sheets

One formula, live verified data in a sheet (re-fetches on open):

=IMPORTDATA("https://starwell.dev/api/starwell/v1/sources/fred/series/UNRATE/observations?format=csv&latest=120")

Sources and attribution

Every API response carries the series' license code, license URL, and exact attribution text; the authoritative per-source view is the live catalog. The licensing gate is enforced at the serving layer: a series whose license does not permit redistribution is excluded from the catalog and from /answer, and direct requests for it return 451 Unavailable For Legal Reasons with the license context instead of data.

Values are served as published by the source (current vintage). Revisions are tracked append-only; historical snapshots are on the roadmap as an institutional feature.

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Roadmap: /execute (sandboxed Python as a service) follows the same contract. Questions, keys, pilots: get a key or write to adarsh.verma1992@gmail.com.