Docs/Sources/Unemployment Rate Grounding Data

Unemployment Rate Grounding Data

Get Unemployment Rate by Country

OperationalCredits 2 per callp50 469msFinance

Overview

Unemployment Rate provides annual unemployment data from the World Bank, based on ILO (International Labour Organization) modeled estimates. The data covers virtually every country in the world and is updated annually. Use this for economic analysis, country comparisons, and labor market research. With changes=true each reading is set against the country's own stored history: the direction of the move for every plan, and on paid plans the previous year and its rate, the change in percentage points over one and five years, and the highest, lowest and average rate over the five years ending at the reading.

Live Test Unemployment Rate Grounding Data Source →

The tool

Once your client is connected to the VerveContext server, this appears in its tool list as UnemploymentRateGroundingData. 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.

Tool call
{
  "name": "UnemploymentRateGroundingData",
  "arguments": {
    "country": "USA"
  }
}

You do not name the tool yourself; the model picks it. Asking about USA in the terms this source covers is enough for it to reach for UnemploymentRateGroundingData on its own — naming it explicitly also works, and is the way to force the call.

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"
    }
  }
}

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.

ArgumentTypeDescription
countryRequiredstringISO country code (2 or 3 letter). Examples: US, USA, DE, DEU, GB, GBR
length 2–3
yearOptionalPremiumintegerSpecific year to retrieve data for (1991-present). Returns latest if not specified.
range 1991–2030
changesOptionalbooleanInclude the change against the previous year, the 5-year change and the 5-year high, low and average rate

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.

Result
{
  "status": "ok",
  "error": null,
  "data": {
    "country": "USA",
    "countryName": "United States",
    "year": 2025,
    "count": 1,
    "historical": [
      {
        "year": 2025,
        "rate": 4.2
      }
    ],
    "previousYear": 2024,
    "changeDirection": "up",
    "previousRate": 4.02,
    "change1y": 0.18,
    "change5y": -3.85,
    "high5y": 5.35,
    "low5y": 3.64,
    "average5y": 4.172
  },
  "code": 200
}

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.

FieldTypeExampleDescription
countrystringUSAISO code representing the country queried
countryNamestringUnited StatesFull official name of the country
yearnumber2025Year of the unemployment data returned
countnumber1Number of historical records available
historicalPremiumarray[1]Array of historical unemployment rates by year
historical.0.yearPremiumnumber2025Year for historical unemployment record
historical.0.ratePremiumnumber4.2Unemployment rate as percentage of labor force
previousYearPremiumnumber2024Year of the previous unemployment record, the year before the reading (with changes=true)
changeDirectionstringupWhether unemployment rose, fell or held against the previous year: up, down or unchanged (with changes=true)
previousRatePremiumnumber4.02Unemployment rate for the previous year, as a percentage of the labor force (with changes=true)
change1yPremiumnumber0.18Change in percentage points from the previous year's rate (with changes=true)
change5yPremiumnumber-3.85Change in percentage points from the rate five years earlier (with changes=true)
high5yPremiumnumber5.35Highest annual rate in the five years ending at the reading; null unless all five are reported (with changes=true)
low5yPremiumnumber3.64Lowest annual rate in the five years ending at the reading; null unless all five are reported (with changes=true)
average5yPremiumnumber4.172Average annual rate over the five years ending at the reading; null unless all five are reported (with changes=true)

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 countryName: 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.

StatusWhat it means
400 / 422The arguments did not validate. The message names the offending one.
401The OAuth session is invalid or expired — reconnect the server.
403Blocked by a key restriction or an IP allow-list. Never a bad identity.
404This source is not part of VerveContext. Check the catalog.
429Out of credits, or a brief rate limit. The message tells them apart.

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

Economic Analysis
Analyze unemployment trends to understand economic health and labor market conditions
Country Comparison
Compare unemployment rates across different countries and regions
Historical Research
Track unemployment changes over time to study economic cycles and policy impacts
Investment Research
Factor unemployment data into investment decisions and economic forecasting

Other ways to use Unemployment Rate Grounding Data

Set up Unemployment Rate 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.

Call it as a REST APIOne HTTPS endpoint and an x-api-key header, with SDKs for Node, Python and .NET.APIVerve →Reference →
Give it to an AI agentConnect over MCP and your agent calls it as a native tool — Claude, Cursor, ChatGPT.VerveKit →Reference →
Google Sheets or ExcelA =VERVE() formula fills a column — no script, no export, recalculates in place.VerveSheets →Reference →

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