# usfiscaldata

> Query the U.S. Treasury Fiscal Data REST API for federal financial data including national debt, daily and monthly treasury statements, securities auctions, interest rates, exchange rates, savings bonds, and government revenue and spending statistics. No API key required.

- Skill: `k-dense-ai/usfiscaldata` (Agent Skill, multi-file: 9 files)
- Install (CLI): `npx skillmds add k-dense-ai/usfiscaldata`
- Raw SKILL.md: https://api.skillmd.com/api/skills/k-dense-ai/usfiscaldata/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Finance & Business, Data & Analytics, SQL & Databases
- Tags: Exchange Rates, Fiscal Data, Interest Rates, National Debt, Rest Api, Savings Bonds, Treasury Securities, Us Treasury
- License: MIT
- Author: K-Dense AI (https://skillmd.com/u/k-dense-ai)
- Updated: 2026-07-06
- Page: https://skillmd.com/skills/k-dense-ai/usfiscaldata

---


# U.S. Treasury Fiscal Data API

Free, open REST API from the U.S. Department of the Treasury for federal financial data. No API key or registration required.

**Base URL:** `https://api.fiscaldata.treasury.gov/services/api/fiscal_service`

Browse [54 datasets and 179 data tables](https://fiscaldata.treasury.gov/datasets/) via the dataset search. Verify endpoint paths on each dataset's API Quick Guide — paths change over time.

## Installation

```bash
uv pip install requests pandas
```

## Quick Start

```python
import requests
import pandas as pd

BASE_URL = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service"

# Get the current national debt (Debt to the Penny)
resp = requests.get(f"{BASE_URL}/v2/accounting/od/debt_to_penny", params={
    "sort": "-record_date",
    "page[size]": 1
})
data = resp.json()["data"][0]
print(f"Total public debt as of {data['record_date']}: ${float(data['tot_pub_debt_out_amt']):,.0f}")
```

```python
# Get Treasury exchange rates for recent quarters
resp = requests.get(f"{BASE_URL}/v1/accounting/od/rates_of_exchange", params={
    "fields": "country_currency_desc,exchange_rate,record_date",
    "filter": "record_date:gte:2024-01-01",
    "sort": "-record_date",
    "page[size]": 100
})
df = pd.DataFrame(resp.json()["data"])
```

## Authentication

None required. The API is fully open and free.

## Core Parameters

| Parameter | Example | Description |
|-----------|---------|-------------|
| `fields=` | `fields=record_date,tot_pub_debt_out_amt` | Select specific columns |
| `filter=` | `filter=record_date:gte:2024-01-01` | Filter records |
| `sort=` | `sort=-record_date` | Sort (prefix `-` for descending) |
| `format=` | `format=json` | Output format: `json`, `csv`, `xml` |
| `page[size]=` | `page[size]=100` | Records per page (default 100) |
| `page[number]=` | `page[number]=2` | Page index (starts at 1) |

**Filter operators:** `lt`, `lte`, `gt`, `gte`, `eq`, `in`

```python
# Multiple filters separated by comma
"filter=country_currency_desc:in:(Canada-Dollar,Mexico-Peso),record_date:gte:2024-01-01"
```

## Key Datasets & Endpoints

### Debt

| Dataset | Endpoint | Frequency |
|---------|----------|-----------|
| Debt to the Penny | `/v2/accounting/od/debt_to_penny` | Daily |
| Historical Debt Outstanding | `/v2/accounting/od/debt_outstanding` | Annual |
| Schedules of Federal Debt | `/v1/accounting/od/schedules_fed_debt` | Monthly |

### Daily & Monthly Statements

| Dataset | Endpoint | Frequency |
|---------|----------|-----------|
| DTS Operating Cash Balance | `/v1/accounting/dts/operating_cash_balance` | Daily |
| DTS Deposits & Withdrawals | `/v1/accounting/dts/deposits_withdrawals_operating_cash` | Daily |
| Monthly Treasury Statement (MTS) | `/v1/accounting/mts/mts_table_1` (18 tables — see [datasets-fiscal.md](references/datasets-fiscal.md)) | Monthly |

### Interest Rates & Exchange

| Dataset | Endpoint | Frequency |
|---------|----------|-----------|
| Average Interest Rates on Treasury Securities | `/v2/accounting/od/avg_interest_rates` | Monthly |
| Treasury Reporting Rates of Exchange | `/v1/accounting/od/rates_of_exchange` | Quarterly |
| Interest Expense on Public Debt | `/v2/accounting/od/interest_expense` | Monthly |

### Securities & Auctions

| Dataset | Endpoint | Frequency |
|---------|----------|-----------|
| Treasury Securities Auctions Data | `/v1/accounting/od/auctions_query` | As Needed |
| Treasury Securities Upcoming Auctions | `/v1/accounting/od/upcoming_auctions` | As Needed |
| Treasury Securities Buybacks | `/v1/accounting/od/buybacks_operations` | As Needed |

### Savings Bonds

| Dataset | Endpoint | Frequency |
|---------|----------|-----------|
| I Bonds Interest Rates | `/v1/accounting/od/i_bonds_interest_rates` | Semi-Annual |
| Savings Bonds Issues, Redemptions & Maturities | `/v1/accounting/od/savings_bonds_report` | Monthly |

## Response Structure

```json
{
  "data": [...],
  "meta": {
    "count": 100,
    "total-count": 3790,
    "total-pages": 38,
    "labels": {"field_name": "Human Readable Label"},
    "dataTypes": {"field_name": "STRING|NUMBER|DATE|CURRENCY"},
    "dataFormats": {"field_name": "String|10.2|YYYY-MM-DD"}
  },
  "links": {"self": "...", "first": "...", "prev": null, "next": "...", "last": "..."}
}
```

**Note:** All values are returned as strings. Convert as needed (e.g., `float()`, `pd.to_datetime()`). Null values appear as the string `"null"`.

## Common Patterns

### Load all pages into a DataFrame

Use the bounded `fetch_all()` helper in [parameters.md](references/parameters.md). For small result sets, a single request with `page[size]=10000` may suffice when `meta.total-pages` is 1.

```python
# Single-page fetch when total-pages == 1
params = {"sort": "-record_date", "page[size]": 10000}
resp = requests.get(f"{BASE_URL}/v2/accounting/od/debt_outstanding", params=params)
result = resp.json()
if result["meta"]["total-pages"] > 1:
    raise ValueError("Use fetch_all() from parameters.md for multi-page results")
df = pd.DataFrame(result["data"])
```

### Aggregation (automatic sum)

Omitting grouping fields triggers automatic aggregation:

```python
# Sum all deposits/withdrawals by record_date and transaction type
resp = requests.get(f"{BASE_URL}/v1/accounting/dts/deposits_withdrawals_operating_cash", params={
    "fields": "record_date,transaction_type,transaction_today_amt"
})
```

## Reference Files

- **[api-basics.md](references/api-basics.md)** — URL structure, HTTP methods, versioning, data types
- **[parameters.md](references/parameters.md)** — All parameters with detailed examples and edge cases
- **[datasets-debt.md](references/datasets-debt.md)** — Debt datasets: Debt to the Penny, Historical Debt, Schedules of Federal Debt, TROR
- **[datasets-fiscal.md](references/datasets-fiscal.md)** — Daily Treasury Statement, Monthly Treasury Statement, revenue, spending
- **[datasets-interest-rates.md](references/datasets-interest-rates.md)** — Average interest rates, exchange rates, TIPS/CPI, certified interest rates
- **[datasets-securities.md](references/datasets-securities.md)** — Treasury auctions, savings bonds, SLGS, buybacks
- **[response-format.md](references/response-format.md)** — Response objects, error handling, pagination, response codes
- **[examples.md](references/examples.md)** — Python, R, and pandas code examples for common use cases