Get foreign-exchange rates for a base currency on a specific past date (YYYY-MM-DD). ECB publishes rates on business days; a weekend/holiday date returns the most recent prior business day.
| Name | Required | Description | Default |
|---|---|---|---|
| base | No | 3-letter base (default USD) | |
| date | Yes | YYYY-MM-DD | |
| symbols | No | Optional comma-separated targets |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full behavioral disclosure responsibility. It clearly discloses the ECB source and the important fallback behavior for weekends/holidays, which is exactly the kind of context an agent needs. For a read-only lookup, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The core action comes first, followed by the single most valuable behavioral caveat about business days. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple historical lookup with fully documented parameters and no output schema, the description provides the essential context: the data source and the prior-business-day fallback. It does not describe the response format, but that gap is minor for this tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter (base, date, symbols) already has a definition. The tool description adds no parameter-specific meaning beyond the schema; it merely restates the date format, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('get'), resource ('foreign-exchange rates'), and scope ('specific past date'), making the tool's function clear. It does not explicitly name sibling tools, but 'specific past date' implicitly distinguishes it from current-rate or time-series tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives like fx_rates or fx_timeseries. The historical-date framing implies usage, but no exclusions or sibling tool mentions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a clearly distinct function: currency conversion, listing supported currencies, historical rates for a single date, latest rates, and time-series analysis. There is no meaningful overlap or ambiguity between the tool purposes.
All tools share the consistent 'fx_' prefix and use snake_case, making the set feel cohesive. Minor inconsistency exists because some names are verbs (convert) while others are nouns (rates, currencies), but the pattern is still predictable and readable.
Five tools form a well-scoped set for a foreign-exchange reference data server. Each tool earns its place by covering a distinct common FX lookup scenario without unnecessary redundancy.
The surface covers the core FX workflows: current rates, historical rates, time series, conversion, and currency metadata. Minor gaps exist, such as no explicit inverse-rate calculation or multiple base currencies in one request, but these are easily worked around with the provided convert and rates tools.