Convert an amount from one currency to another at the latest ECB reference rate. Returns the rate, the converted result, and the rate date.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target 3-letter currency | |
| from | Yes | Source 3-letter currency | |
| amount | Yes | Amount in the 'from' currency to convert. Send it as a number, not a string. |
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 must carry behavioral disclosure on its own. It does state the rate source (ECB reference rate) and the return payload (rate, converted result, rate date), which is good. But it omits potential nuances such as ECB rate lag or business-day staleness, and does not explicitly confirm the operation is read-only.
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?
A single sentence leads with the action and resource, then summarizes the output. Every word carries information; there is no repetition of the tool name or schema descriptions.
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?
The tool is simple, and the description covers the core operation and return fields, which partially compensates for the missing output schema. However, it leaves out edge cases like unsupported currency codes, rate availability timing, or how 'latest' relates to ECB publication dates. These gaps are notable when no annotations or output schema exist.
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 all three parameters (amount, from, to) are already documented in the input schema. The description adds no parameter-level meaning beyond the schema, so the baseline 3 is appropriate.
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 uses a specific verb ('Convert'), identifies the exact resource (amount between currencies), and names the data source ('latest ECB reference rate'). This clearly differentiates it from siblings like fx_historical and fx_timeseries, which serve different time-range purposes.
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 intended use is implied by the verb and resource: convert an amount at the current or latest rate. However, it does not explicitly tell the agent when to choose this over fx_historical, fx_rates, or fx_timeseries, and provides no 'when not to use' guidance.
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.