Skip to main content
Glama

exchange-rates-mcp-server

Fx Convert Currency

fx_convert_currency
Read-onlyIdempotent

Convert an amount between any two currencies at the latest or a historical rate. Returns the converted amount, the rate used, the actual rate date, and whether the date was snapped from a weekend/holiday to the prior business day. Cross-rates are triangulated through EUR automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoISO 8601 date (YYYY-MM-DD) for a historical rate. Omit for the latest available rate. ECB data starts 1999-01-04. Future dates are not supported.
amountYesAmount in the base currency to convert. Must be greater than zero.
base_currencyYesISO 4217 source currency code (e.g. USD). Call fx_list_currencies to get valid codes.
quote_currencyYesISO 4217 target currency code (e.g. EUR). The amount will be expressed in this currency.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rateNoExchange rate used: units of quote currency per 1 unit of base currency.
errorNoPresent when the call failed. Absent on success.
sourceNoAlways "ECB via Frankfurter" — the upstream data provider.
rate_dateNoActual date of the rate used for conversion.
rate_typeNoAlways "ECB reference (mid-market)" — these are reference rates, not tradeable bid/ask.
base_amountNoThe input amount in the base currency.
date_snappedNoTrue when the API returned a different date than requested — ECB silently snaps weekend/holiday requests to the prior business day.
quote_amountNoThe converted amount in the quote currency, rounded to 6 decimal places.
base_currencyNoSource currency code.
quote_currencyNoTarget currency code.

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable behavioral context beyond that: the weekend/holiday snapping behavior, the exact return fields (rate, actual date, snap flag), and automatic EUR triangulation. No contradictions 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.

Conciseness5/5

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

Two tightly written sentences with zero filler. The primary purpose is front-loaded, and the return behavior is summarized in one breath. Every clause earns its place.

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

Completeness5/5

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

For a conversion tool with a well-populated schema and an output schema, this description covers all essential behavioral aspects: return values, date snapping, triangulation, and the optional nature of the date parameter. No missing information the agent needs to invoke it correctly.

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

Parameters3/5

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

Schema coverage is 100% with rich descriptions for all four parameters, so the schema does the heavy lifting. The description adds negligible parameter-level detail beyond what the schema already provides (e.g., date handling, amount constraints, currency code reference). Baseline 3 is appropriate.

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?

Description states a specific verb-resource pair ('Convert an amount between any two currencies') and differentiates from sibling rate-getters by framing the action as conversion, not just rate retrieval. It also lists what it returns, making the tool's role 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 clearly implies usage for conversions (as opposed to rate-only queries like fx_get_rate) and mentions automatic EUR triangulation, but it does not explicitly name alternatives or state when to prefer this over siblings. The context is sufficient without being explicit about exclusions.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.6/5.0
Disambiguation5/5

Each tool has a distinct, non-overlapping purpose: conversion, single rate, bulk rates, timeseries, currency listing, and DataFrame inspection/query. The descriptions clearly differentiate between getting a rate vs converting an amount, and between inline vs DataCanvas-stored timeseries.

Naming Consistency5/5

All tools follow a consistent fx_verb_noun pattern (e.g., fx_get_rate, fx_convert_currency, fx_list_currencies). The two dataframe tools also adhere to fx_dataframe_verb, maintaining a uniform convention across the entire set.

Tool Count5/5

Seven tools is well-scoped for an exchange-rate server. Each tool addresses a needed operation (conversion, rates, timeseries, metadata) without redundancy or bloat, and adding DataFrame analysis feels justified for handling large datasets.

Completeness5/5

The surface covers the full lifecycle of exchange-rate queries: listing currencies, fetching single or bulk rates, converting with historical dates, and retrieving timeseries. The optional DataCanvas integration fills the gap for large-range analysis, leaving no obvious dead ends for common use cases.