Skip to main content
Glama
JerBouma

Finance Toolkit

by JerBouma

rates

Read-onlyIdempotent

Access central bank policy benchmarks, government bond yields, mortgage costs, and inflation expectations with rolling, trailing, and growth calculations.

Instructions

Interest rate data (central bank policy rates, short/long-term rates, government bond yields, ICE BofA corporate bond series, EURIBOR, ECB rates, Federal Reserve rates, official U.S. Treasury par yield curve, yield curve slope). 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. The central bank policy rate, short/long-term rate, and yield curve slope indicators additionally support rolling=N (moving-average smoothing) and trailing=N (trailing N-period sum). Also includes get_mortgage_rate_30_year, get_real_yield_curve (FRED TIPS real yields) and get_breakeven_inflation_expectations — three US-only FRED-backed indicators. A FRED API key is optional and free (get one at https://fred.stlouisfed.org/docs/api/api_key.html); without it these three return no data, while get_treasury_rates and every other indicator in this tool work without one. FRED-backed indicators only return a 'United States' column regardless of the countries= argument.

Available indicators: get_central_bank_policy_rate, get_short_term_interest_rate, get_long_term_interest_rate, get_government_bond_yield, get_euribor_rates, get_european_central_bank_rates, get_federal_reserve_rates, get_ice_bofa_effective_yield, get_ice_bofa_option_adjusted_spread, get_ice_bofa_total_return, get_ice_bofa_yield_to_worst, get_mortgage_rate_30_year, get_real_yield_curve, get_breakeven_inflation_expectations, g

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lagNoNumber of periods to lag when computing growth rates.
rateNoValue for rate. Leave unset to use the default of the indicator you selected. Defaults are 'EFFR' for get_federal_reserve_rates; None for get_european_central_bank_rates.
growthNoReturn period-over-period growth rates instead of absolute values.
periodNoObservation frequency, e.g. 'monthly', 'quarterly', or 'annual'.
nominalNoValue for nominal.
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.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-08-19
maturityNoValue for maturity.
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.
maturitiesNoComma-separated bond maturity labels, e.g. '3month,2year,10year'.
short_termNoValue for short_term.
start_dateNoStart of the date range in YYYY-MM-DD format.2021-08-20
gmdb_sourceNoUse the Global Macro Database as the data source when True, rather than the OECD. The two are independent providers with different country and period coverage; both return rates and ratios as decimal fractions.
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.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, and the description adds meaningful behavioral context: FRED-backed indicators return no data without an API key, only return a 'United States' column, and rolling/trailing have specific smoothing/sum semantics. No contradiction with annotations.

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

Conciseness2/5

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

The description is information-dense but overly long and poorly structured as a single wall of text. The 'Available indicators' list duplicates the enum in the input schema and is truncated mid-word ('g'), which is a structural defect. It could be tightened with headers and by removing redundant enumeration.

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 a tool with 16 indicators and 18 parameters, the description covers the most important cross-cutting constraints: country requirements, ticker prohibition, FRED API key dependency, and rolling/trailing behavior. The output schema and rich input schema cover the remaining details, so the description is complete enough 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 the baseline is 3, but the description adds value beyond the schema by explaining how countries should be used, that tickers= must not be used, and what rolling/trailing mean in practice. This is more than the schema's generic parameter 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 clearly identifies the tool as providing interest rate data and enumerates specific rate families (central bank policy rates, government bond yields, EURIBOR, ECB/Fed rates, Treasury yield curve, etc.), which distinguishes it from sibling tools like fixed_income or government. It lacks an explicit verb like 'retrieve' or 'get', but the resource scope is specific and unambiguous.

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?

The description gives explicit usage constraints: requires countries='United States', forbids tickers=, supports start_date/end_date and quarterly=true, and explains rolling/trailing behavior. It also clarifies the optional FRED API key and which indicators are affected. It does not name sibling tools as alternatives, so it stops short of a 5.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/JerBouma/FinanceToolkit'

If you have feedback or need assistance with the MCP directory API, please join our Discord server