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JerBouma

Finance Toolkit

by JerBouma

environment

Read-onlyIdempotent

Retrieve ESG scores for tickers and carbon footprint or renewable energy data for countries. Supports rolling and trailing windows for time-series analysis.

Instructions

Environmental and ESG data. For ESG scores (E, S, G ratings) use tickers='AAPL'. For carbon footprint and renewable energy data use countries='United States' (also supports rolling=N and trailing=N smoothing/summation). This is the only tool that accepts BOTH tickers= and countries= depending on the indicator.

Available indicators: get_carbon_footprint, get_renewable_energy, get_esg_scores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lagNoNumber of periods to lag when computing growth rates.
growthNoReturn period-over-period growth rates instead of absolute values.
rollingNoRolling 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.
tickersNoComma-separated ticker symbols, e.g. 'AAPL,MSFT,GOOGL'.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-10-02
trailingNoTrailing 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.
countriesNoComma-separated country names, e.g. 'United States,Germany,Japan'.
indicatorYesName of the specific metric to calculate, e.g. 'get_asset_turnover_ratio'. Required — omitting it returns the list of available indicators.
quarterlyNoReturn quarterly data instead of annual when True.
start_dateNoStart of the date range in YYYY-MM-DD format.2021-10-03
standardizeNoReturn 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_columnsNoComma-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.
benchmark_tickerNoTicker used as the market benchmark, e.g. 'SPY' or '^GSPC'.SPY

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.2.1
    • 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"
  2. Changed2 schema fields changedv2.2.0
    • 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"
  3. Changed5 schema fields changed
    • 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"
      +}
  4. Changed2 schema fields changedv2.1.4
    • 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"
  5. Changed2 schema fields changedv2.1.3
    • 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"
  6. Changed4 schema fields changedv0.1.2
    • 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"
  7. Addedv0.1.1

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description adds useful dispatch behavior (tickers vs countries, indicator acting as a sub-selector) but says nothing about pagination, date-range defaults, or result-shaping behavior beyond what the schema already documents.

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?

Three short sentences, front-loaded with the domain and immediately followed by the parameter-routing rules and the indicator list. Minimal waste; the indicator enumeration is somewhat redundant with the enum in the schema but aids quick scanning.

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?

With an output schema present, return-value detail is unnecessary, and the 13-parameter schema is fully self-documented. The description covers the essential decision (which of the three indicators and which entity parameter), leaving only minor gaps around date defaults and smoothing behavior that the schema handles.

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?

Although schema coverage is 100%, the description adds cross-parameter semantics the schema cannot express: tickers= applies to ESG scores while countries= applies to carbon/renewable indicators, and it highlights that this tool uniquely accepts both. That is meaningfully more than the per-field descriptions provide.

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

Purpose4/5

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

The description opens with a specific domain statement ('Environmental and ESG data') and enumerates the three indicators the tool exposes, so an agent knows this is ESG/carbon/renewables, not general financial data. It does not explicitly contrast with sibling categories like macroeconomics or market_data, but the domain is unmistakable.

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?

It gives concrete usage conditions: 'For ESG scores use tickers=...', 'For carbon footprint and renewable energy use countries=...', and notes rolling/trailing support. This is real routing guidance that maps indicator to parameter, though it never names an alternative sibling tool or states when NOT to use this one.

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