Finance Toolkit

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government

Read-onlyIdempotent

Retrieve country fiscal metrics such as debt, deficit, expenditure, revenue, tax revenue, and trust using country names, date ranges, quarterly data, rolling or trailing windows.

Instructions

Government fiscal metrics by country (debt, deficit, expenditure, revenue, tax revenue, trust in government). Requires countries='United States' — use comma-separated values for multiple countries. Do NOT use tickers= for this tool. Supports start_date/end_date and quarterly=true. Supports rolling=N (moving-average smoothing) and trailing=N (trailing N-period sum, e.g. a trailing-4-quarter sum) on the raw series.

Available indicators: get_government_debt, get_government_debt_to_gdp_ratio, get_government_deficit, get_government_deficit_to_gdp_ratio, get_government_expenditure, get_government_expenditure_to_gdp_ratio, get_government_revenue, get_government_revenue_to_gdp_ratio, get_government_tax_revenue, get_government_tax_revenue_to_gdp_ratio, get_trust_in_government.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`lag`	No	Number of periods to lag when computing growth rates.
`growth`	No	Return period-over-period growth rates instead of absolute values.
`rolling`	No	Rolling window size in number of periods. When set, the metric is computed over a smoothly overlapping trailing window across the full history (e.g. period='monthly' and rolling=6 gives a rolling 6-month value) instead of one value per period, or (for economics indicators) a simple moving average used to smooth the raw series.
`end_date`	No	End of the date range in YYYY-MM-DD format.	2026-10-02
`trailing`	No	Trailing window size in number of periods. Sums the raw values over the trailing N periods (e.g. trailing=4 on quarterly data gives a trailing-4-quarter / TTM-style sum) instead of returning one value per period.
`countries`	No	Comma-separated country names, e.g. 'United States,Germany,Japan'.
`indicator`	Yes	Name of the specific metric to calculate, e.g. 'get_asset_turnover_ratio'. Required — omitting it returns the list of available indicators.
`quarterly`	No	Return quarterly data instead of annual when True.
`start_date`	No	Start of the date range in YYYY-MM-DD format.	2021-10-03
`standardize`	No	Return the Z-Score (standard score) instead of the raw values, i.e. how many standard deviations each value is from the mean of its own series. When combined with growth=True, the growth values are standardized instead of the raw values.
`show_columns`	No	Comma-separated names to filter the output. For historical data use the key names visible in any response record (e.g. 'Close,Volume,Return'). For financial statements use the 'metric' field values from the response (e.g. 'Revenue,Net Income,EBITDA'). Call the tool once without this parameter to see all available names, then repeat with show_columns to reduce response size and token usage.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv2.2.1Oct 2, 2026
- changedInput schema / properties / end_date / default
```
Previous value: -"2026-08-19"New value: +"2026-10-02"
```
- changedInput schema / properties / start_date / default
```
Previous value: -"2021-08-20"New value: +"2021-10-03"
```
Changed2 schema fields changedv2.2.0Aug 19, 2026
- changedInput schema / properties / end_date / default
```
Previous value: -"2026-07-14"New value: +"2026-08-19"
```
- changedInput schema / properties / start_date / default
```
Previous value: -"2021-07-15"New value: +"2021-08-20"
```

Changed5 schema fields changedJul 14, 2026

changedInput schema / properties / end_date / default

Previous value: -"2026-07-09"New value: +"2026-07-14"

addedInput schema / properties / rolling

Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Rolling window size in number of periods. When set, the metric is computed over a smoothly overlapping trailing window across the full history (e.g. period='monthly' and rolling=6 gives a rolling 6-month value) instead of one value per period, or (for economics indicators) a simple moving average used to smooth the raw series.",
+  "title": "Rolling"
+}

addedInput schema / properties / standardize

Added value: +{
+  "default": false,
+  "description": "Return the Z-Score (standard score) instead of the raw values, i.e. how many standard deviations each value is from the mean of its own series. When combined with growth=True, the growth values are standardized instead of the raw values.",
+  "title": "Standardize",
+  "type": "boolean"
+}

changedInput schema / properties / start_date / default

Previous value: -"2021-07-10"New value: +"2021-07-15"

addedInput schema / properties / trailing

Added value: +{
+  "anyOf": [
+    {
+      "type": "integer"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Trailing window size in number of periods. Sums the raw values over the trailing N periods (e.g. trailing=4 on quarterly data gives a trailing-4-quarter / TTM-style sum) instead of returning one value per period.",
+  "title": "Trailing"
+}

Changed2 schema fields changedv2.1.4Jul 9, 2026
- changedInput schema / properties / end_date / default
```
Previous value: -"2026-06-27"New value: +"2026-07-09"
```
- changedInput schema / properties / start_date / default
```
Previous value: -"2021-06-28"New value: +"2021-07-10"
```
Changed2 schema fields changedv2.1.3Jun 27, 2026
- changedInput schema / properties / end_date / default
```
Previous value: -"2026-06-23"New value: +"2026-06-27"
```
- changedInput schema / properties / start_date / default
```
Previous value: -"2021-06-24"New value: +"2021-06-28"
```

Changed4 schema fields changedv0.1.2Jun 23, 2026

changedInput schema / properties / end_date / default

Previous value: -"2026-06-22"New value: +"2026-06-23"

removedInput schema / properties / rounding

Removed value: -{
-  "anyOf": [
-    {
-      "type": "integer"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "Number of decimal places to round results to.",
-  "title": "Rounding"
-}

addedInput schema / properties / show_columns

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Comma-separated names to filter the output. For historical data use the key names visible in any response record (e.g. 'Close,Volume,Return'). For financial statements use the 'metric' field values from the response (e.g. 'Revenue,Net Income,EBITDA'). Call the tool once without this parameter to see all available names, then repeat with show_columns to reduce response size and token usage.",
+  "title": "Show Columns"
+}

changedInput schema / properties / start_date / default

Previous value: -"2021-06-23"New value: +"2021-06-24"

Addedv0.1.1Jun 22, 2026

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so safety is covered. The description adds operationally important context beyond that: the tickers= prohibition, the countries-required constraint, and how rolling/trailing transform the returned series (moving average vs trailing sum). It stops short of describing return shape, which is acceptable given an output schema exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose and hard constraints before the indicator enumeration; every sentence carries practical information. The enumerated indicator list is somewhat redundant with the schema enum, costing a little conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter tool with an output schema, the description covers the non-obvious constraints (countries required, no tickers, quarterly/rolling/trailing behavior). Remaining params (lag, growth, standardize, show_columns) are adequately documented in the schema, so nothing critical is missing for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline would be 3, but the description adds real meaning: it warns that countries is effectively required despite the schema default of empty string, and clarifies the rolling (smoothing) vs trailing (N-period sum) distinction with a concrete quarterly example. The indicator list merely duplicates the enum, which does not earn extra credit.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource class (government fiscal metrics by country) and enumerates the exact metrics available, so an agent can immediately see this covers debt/deficit/expenditure/revenue/tax/trust rather than generic macro data. It is clearly distinguishable from siblings like macroeconomics, rates, and fixed_income.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete usage rules: countries must be specified (with a literal example), do NOT use tickers=, and how to enable quarterly/rolling/trailing. It does not, however, say when to prefer this tool over sibling tools such as macroeconomics or rates, so routing among siblings is left partly to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.