Get latest foreign exchange rates for a base currency via Frankfurter API. Returns: {base, date, rates: {EUR: 0.92, ...}}
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "get_exchange_rates"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| base | No | USD |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It reveals the return format and implies a read-only operation, but does not disclose potential limitations such as supported currencies, rate update frequency, or any API restrictions. The mention of 'Frankfurter API' gives some context but is insufficient for full transparency.
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 extremely concise: two sentences totaling 20 words. The first sentence states the purpose and data source, the second shows the return format. Every word is necessary with no redundancy.
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 one-parameter tool with no output schema and no annotations, the description provides essential information: what it does, what it returns, and the source. It lacks details like supported currency codes or error handling, but these are not critical for basic usage. The context signals suggest this tool is low complexity, making the description largely adequate.
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?
The input schema only defines the 'base' parameter with a default of USD, leaving its purpose unclear. The description adds meaning by stating it is the base currency for which rates are fetched. However, it does not specify that the value must be a three-letter ISO currency code, which would further aid agents.
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 clearly states the tool retrieves latest foreign exchange rates for a base currency via the Frankfurter API. This specific verb-resource combination effectively distinguishes it from sibling tools like convert_currency (which converts amounts) and get_crypto_price (which deals with cryptocurrencies).
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 does not provide any guidance on when to use this tool versus alternatives such as convert_currency or get_crypto_price. It lacks explicit usage context, like suggesting this tool for obtaining rate lists before calling convert_currency for conversions.
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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