currencybrapi.dev — currency conversion rate for a pair (e.g. 'USD-BRL'): current bid/ask rate and daily change. Covers major pairs against BRL and other currencies.
| Name | Required | Description | Default |
|---|---|---|---|
| currency | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds useful context about the return data (bid/ask, daily change) and scope (major pairs against BRL), but does not disclose potential limitations like rate limits or error handling. No contradiction with annotations.
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, information-dense sentence that front-loads the core purpose and includes an example. Every part earns its place, with no wasted words.
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 has an output schema and annotations covering safety, but the description is incomplete due to the ambiguous parameter semantics. It does mention the return values (bid/ask, daily change) and scope, but the confusion about whether the parameter is a single currency or a pair prevents a complete understanding.
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 0%, so the description must explain the parameter. It explicitly says 'pair (e.g. 'USD-BRL')', implying the parameter should be a pair string. However, the schema property is named 'currency' with examples 'USD' and 'EUR' (single codes), creating ambiguity and conflicting cues about the required input format.
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's function: 'currency conversion rate for a pair (e.g. 'USD-BRL')' with specific outputs (bid/ask rate and daily change). It distinguishes from siblings like crypto or quote by focusing on fiat currency pairs and mentioning the data source 'brapi.dev'.
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 implies usage for currency conversion but provides no explicit alternatives or exclusions. It does not mention when to use this tool instead of sibling tools like 'crypto' or 'quote', leaving the agent to infer from the name and context.
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.
Most tools fall into recognizable families (data lookup, entity research, prediction markets, memory, subscriptions), and the detailed descriptions help separate them. However, ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants, and several polymarket scanning tools overlap in purpose enough to cause misselection.
Nearly all tool names are snake_case and readable, and families share clear prefixes like ask_pipeworx_*, polymarket_*, and pipeworx_*. The main inconsistency is that the Brazilian data endpoints use bare nouns (quote, crypto, currency, inflation, prime_rate) while most other tools use verb-like action names, so there is no single verb_noun pattern throughout.
38 tools is well above the 25+ threshold for a heavy MCP surface, even though the server aggregates several distinct domains. Each tool may have a purpose, but the sheer count makes the set difficult to navigate and suggests the server is trying to be a platform rather than a focused toolset.
The server covers the full lifecycle for its core areas: lookup (ask_pipeworx, grounded, deep_research), entity workflows (resolve, profile, compare, recent_changes), memory (remember/recall/forget), and subscriptions (subscribe/list/unsubscribe/recent_alerts). Minor gaps exist, such as no subscription update/pause and no direct tool to fetch an arbitrary pipeworx:// citation, but agents can work around these.