Convert an amount between currencies using cached ECB exchange rates.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target currency code (ISO 4217) | |
| from | Yes | Source currency code (ISO 4217) | |
| amount | Yes | Amount to convert |
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?
No annotations are provided, so the description carries the disclosure burden. It does mention 'cached' exchange rates, which hints at potential staleness, but it does not disclose limitations like invalid currency handling, rounding behavior, or whether rates are updated. This is partial but not comprehensive behavioral 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 a single, efficient sentence that starts with the primary verb 'Convert' and provides the essential resource and data source without any wasted words. It is perfectly sized for its purpose.
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?
Given the tool's simplicity (3 fully described parameters), the description adequately conveys the core function and data source. There is no output schema, so a note on return format would be nice, but the tool is straightforward enough that this absence does not hinder usability. The mention of caching adds important context for accuracy expectations.
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 already provides full descriptions for all three parameters (amount, from, to) with ISO 4217 codes and exclusivity constraints. The description adds the 'cached ECB' context but does not introduce any additional parameter-level meaning beyond the schema, so the baseline of 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 clearly states the verb 'convert' and the resource 'amount between currencies', and adds the specific data source 'cached ECB exchange rates'. This distinguishes it from sibling tools like convert_timezone and makes the tool's purpose unmistakable.
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 clear context by specifying it converts an amount between currencies, and the mention of 'cached ECB exchange rates' implies when it applies (currency conversion). No explicit exclusions are needed since there is no direct competing currency tool among siblings, and this context is sufficient for selection.
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 has a distinct purpose and target resource or operation. While some tools are thematically related (e.g., detect_secrets and classify_gdpr both analyze text), their specific outputs and use cases are clearly separated by names and descriptions.
Most tools follow a clear verb_noun pattern (convert_currency, generate_uuid, validate_iban), and the noun_to_noun conversion tools (csv_to_json, html_to_text) form a consistent sub-pattern. The mix of verb_noun and X_to_Y is understandable and predictable, though not uniform.
23 tools is on the higher end for a utility server, feeling like a grab-bag of many unrelated functions. While each tool is simple and serves a purpose, the count exceeds the typical well-scoped range, making it heavier than ideal.
The tool coverage is broad but scattered with no clear domain focus. Obvious complementary utilities are missing, such as URL encoding/decoding, YAML conversion, or PDF generation. However, within each small category, core operations are present, so agents can work around gaps.