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exchange-rates-mcp-server

Fx List Currencies

fx_list_currencies
Read-onlyIdempotent

List all supported ISO 4217 currency codes with their full names. Call this before converting to disambiguate "dollars" (USD vs AUD vs CAD vs HKD vs SGD) or to validate a user-supplied currency code. Covers the ~30 ECB reference currencies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoTotal number of supported currencies.
errorNoPresent when the call failed. Absent on success.
sourceNoAlways "ECB via Frankfurter" — the upstream data provider.
currenciesNoAll supported currencies, sorted alphabetically by code.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds useful context about scope ('~30 ECB reference currencies') and the disambiguation purpose, which is beyond the annotations. No contradictions.

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?

Three sentences, no filler. The main purpose is front-loaded, followed by usage context and scope. Every sentence earns its place, and the description is appropriately sized.

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?

Given the tool has no parameters and an output schema exists, the description covers all needed context: what it returns (codes and names), when to use it (disambiguation/validation), and its scope (ECB currencies). Nothing essential is missing.

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?

With zero parameters, the schema provides no meaningful info to describe, so the baseline is 4. The description doesn't need to add parameter details and correctly stays silent on parameters.

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?

The description states the exact action and resource: 'List all supported ISO 4217 currency codes with their full names.' It also distinguishes itself from conversion tools by explaining its disambiguation role, making it clear this is a lookup/list tool.

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 when-to-use guidance: 'Call this before converting... or to validate a user-supplied currency code.' It does not name specific alternatives or exclusions, but the context is clear that this is for listing/validation prior to conversion, which is sufficient.

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

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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.