quotebrapi.dev — live quote for one or more Brazilian market tickers (comma-separated, e.g. 'PETR4,VALE3'): price, change, volume, and optional OHLC history range/interval and fundamental data.
| Name | Required | Description | Default |
|---|---|---|---|
| range | No | ||
| modules | No | ||
| tickers | Yes | ||
| interval | No | ||
| dividends | No | ||
| fundamental | No |
| 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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that quotes are live and lists the data fields, but it does not mention rate limits, authentication, or any additional behavioral constraints beyond what annotations imply.
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, front-loaded sentence that efficiently conveys the tool's purpose, example, and available data options. No redundant or unnecessary words are present.
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, so return values are covered, and annotations handle safety. However, the description does not explain all parameters (modules, dividends) and shows inconsistent ticker suffix examples ('PETR4' vs 'IBOV11.SA'), which could confuse an agent selecting inputs.
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 compensate. It explains the tickers format and mentions OHLC range/interval and fundamental data, but leaves 'modules' and 'dividends' unexplained. The example shows dividends but gives no semantic detail, leaving a significant gap.
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 fetches live quotes for Brazilian market tickers, including price, change, volume, and optional OHLC and fundamental data. The example with comma-separated tickers makes the purpose concrete, and the 'Brazilian market' scope distinguishes it from sibling financial 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 quote_list, crypto, or currency. The example implies usage for Brazilian stocks, but there are no exclusions, prerequisites, or direct comparisons to sibling tools.
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.