> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vintl.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Vintl API

> Point-in-time macro-economic and treasury data API. One query parameter to see what the data said then, not what it says today.

Every macro data API gives you what the data says **today**.
Vintl gives you what the data said **then**.

<CardGroup cols={3}>
  <Card title="Quickstart" icon="rocket" href="/quickstart">
    First API call in under 2 minutes. Free tier, no credit card.
  </Card>

  <Card title="Point-in-time queries" icon="clock-rotate-left" href="/guides/point-in-time">
    One parameter to query what the data said on any historical date.
  </Card>

  <Card title="API Reference" icon="code" href="/api-reference">
    Interactive playground for every endpoint.
  </Card>
</CardGroup>

## The problem

GDP published on October 26, 2023: **\$22,491B**. That same quarter revised by September 2025: **\$22,841B**. A \$349 billion gap.

If your backtest uses today's numbers, it's using information that didn't exist when the trade would have been placed.

```bash theme={"dark"}
# Add ?as_of= to any macro query. That's all it takes.
curl -H "X-API-Key: YOUR_API_KEY" \
  "https://api.vintl.io/v1/series/GDPC1/observations?as_of=2023-10-26"
```

Returns `"22491.567"` — the advance estimate published that day, not today's revision.

## Data coverage

<CardGroup cols={2}>
  <Card title="Treasury yields" icon="chart-line">
    Daily par and TIPS curves. 14 maturities, 1990-present. Spreads in basis points. Never revised.
  </Card>

  <Card title="Macro indicators" icon="chart-bar">
    GDP, CPI, unemployment, payrolls, fed funds, industrial production, housing starts, PCE. Every revision tracked.
  </Card>

  <Card title="Point-in-time snapshots" icon="clock-rotate-left">
    `?as_of=DATE` on any macro series. Returns exactly what was published on that date.
  </Card>

  <Card title="Revision history" icon="code-compare">
    Full audit trail for every data point. See how GDP moved across 5 revisions over 2 years.
  </Card>
</CardGroup>

## Design principles

<Tabs>
  <Tab title="Stripe-inspired envelope">
    Consistent `object`, `request_id`, `status`, `results` across every endpoint. Cursor pagination. [RFC 9457](https://www.rfc-editor.org/rfc/rfc9457) errors. If you've used Stripe's API, this will feel familiar.
  </Tab>

  <Tab title="Financial precision">
    Values are strings — `"4.39"`, never `4.39`. Decimal arithmetic doesn't lose precision in transit. Dates are ISO 8601. No surprises.
  </Tab>

  <Tab title="AI-native">
    Structured JSON with descriptive field names. Fits in context windows. Works as [function calling output](/guides/ai-agents) for Claude, GPT, or any agent framework.
  </Tab>
</Tabs>

## Start building

<Steps>
  <Step title="Get your API key">
    Sign up at [app.vintl.io](https://app.vintl.io/signup). Free tier: 500 requests/day, no credit card.
  </Step>

  <Step title="Make your first call">
    Follow the [quickstart](/quickstart) — real economic data in one curl command.
  </Step>

  <Step title="Explore point-in-time">
    Read the [point-in-time guide](/guides/point-in-time) to understand the `as_of` parameter.
  </Step>
</Steps>