National Debt Grounding Data

Overview

The collector calls the Treasury's Debt to the Penny dataset every day at 11am and stores one record per Treasury record date, the business days on which the figures are published. `totalDebt` is total public debt outstanding, `publicDebt` is debt held by the public, `intragovernmentalDebt` is debt held by government accounts, and `publicDebtRatio` is publicDebt as a percent of totalDebt, rounded to two decimals.

`perCapita` divides the total by a fixed US population of 335,000,000, which is also what `population` returns, so it is an estimate that does not track census changes. `perHousehold` divides the total by that population over 2.5 people per household.

`date` takes YYYY-MM-DD. When the date has no record, the API searches back up to ten days and returns the nearest earlier one; `date` echoes what you asked for and `recordDate` shows the record actually used. Without `date` you get the newest record.

With `changes=true`, `previousDebt` and `previousDate` are the record before the returned one. `change30d` and `change1y` compare with the record 30 and 365 days back, or the nearest before each. `averageDailyChange30d` divides `change30d` by the calendar days between the two records, so weekends spread the growth instead of inflating it. Dollar changes are rounded to cents; any comparison whose record is missing is null.

Live Test National Debt Grounding Data Source →

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as NationalDebtGroundingData. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.

{
  "name": "NationalDebtGroundingData",
  "arguments": {}
}

Connecting

One server URL covers every source in the catalog, including this one. Authorization is OAuth: the client opens a browser once, and there is no key to paste into a config file.

{
  "mcpServers": {
    "vervecontext": {
      "url": "https://api.vervecontext.com/v1/mcp"
    }
  }
}

https://api.vervecontext.com/v1/mcp

Per-client setup — Claude, Cursor, VS Code, ChatGPT — is on the MCP setup page.

Arguments

These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made. Premium arguments are accepted on every plan but only take effect on plans that include them.

What the model gets back

The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.

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{
  "status": "ok",
  "error": null,
  "data": {
    "date": "2026-10-26",
    "recordDate": "2026-10-26",
    "totalDebt": 40528358939415.85,
    "totalDebtFormatted": "$40.53 trillion",
    "publicDebt": 32635294814294.48,
    "publicDebtFormatted": "$32.64 trillion",
    "intragovernmentalDebt": 7893064125121.37,
    "intragovernmentalDebtFormatted": "$7.89 trillion",
    "perCapita": 120980,
    "perCapitaFormatted": "$120,980",
    "population": 335000000,
    "publicDebtRatio": 80.52,
    "perHousehold": 302450.44,
    "perHouseholdFormatted": "$302,450",
    "previousDebt": 40463151897249.19,
    "previousDate": "2026-10-23",
    "change1d": 65207042166.66,
    "change30d": 431180819664.95,
    "change1y": 2519332979958.45,
    "changePercent1y": 6.6282,
    "averageDailyChange30d": 13909058698.87
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Why ground on it

A model can produce something that looks like this answer from its training data, and be confidently out of date or simply wrong. This source returns the current value in a shape you can check, which is the difference between an answer you can cite and one you have to hedge.

Point an evaluation at recordDate: it is the field most worth pinning a claim to, and it is either present and current or absent — never plausibly invented.

Failure modes

Errors come back as tool errors carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.

A call costs 2 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

Financial Dashboards

Display real-time national debt figures on financial dashboards and economic monitoring tools

Economic Research

Analyze historical debt trends for economic research and policy analysis

Educational Tools

Build educational applications showing government debt and per-capita calculations

News Applications

Provide up-to-date debt figures for news and media applications

Other ways to use National Debt Grounding Data

Set up National Debt Grounding Data on VerveContext, or reach the same source a different way. Your VerveContext account and credits work on all of them — one key, one balance.

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