usfiscaldata

name	usfiscaldata
description	Query the U.S. Treasury Fiscal Data REST API for federal financial data. No API key required. Use for national debt (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates, foreign exchange rates, savings bonds, or U.S. government revenue and spending statistics.
license	MIT
allowed-tools	Read Write Edit Bash
metadata	{"version":"1.1","skill-author":"K-Dense Inc."}

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 via the dataset search. Verify endpoint paths on each dataset's API Quick Guide — paths change over time.

Installation

uv pip install requests pandas

Quick Start

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}")

# 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

# 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)	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

{
  "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":     

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. For small result sets, a single request with page[size]=10000 may suffice when meta.total-pages is 1.

# 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:

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