[Global Equities Screener] Screen Brazil's B3 exchange (São Paulo) — Bovespa Index, Small Caps, full Brazilian universe.
Args: criteria: filter dict (sector, market cap, dividend yield, etc.) limit: max rows to return
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| criteria | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the safety profile is clear. The description adds that the tool screens equities with filter criteria and limit, which is consistent but does not disclose additional behavioral traits like pagination or rate limits. It adds some context but not rich behavioral detail.
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, with a clear front-loaded purpose and a list of arguments. Every sentence serves a purpose with zero 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?
Given the low complexity (2 parameters, simple screening) and presence of annotations (readOnly, openWorld), the description is mostly complete. It explains what the tool does and the parameters, but does not describe the return format or output structure. However, for a screening tool, this is generally acceptable.
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 coverage is 0%, so the description compensates by explaining the criteria parameter as a filter dict with examples (sector, market cap, dividend yield) and the limit parameter as max rows. This adds meaning beyond the schema's type-only definitions, though it could be more precise about allowed keys.
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 it screens Brazil's B3 exchange, specifically mentioning the Bovespa Index and Small Caps, indicating the full Brazilian universe. This provides a specific verb (screen) and resource (Brazil B3), and distinguishes it from sibling country-specific screeners.
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 use for Brazilian equities through its focus on Brazil's B3 exchange. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites. The context of sibling tools suggests usage, but explicit guidance is absent.
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.
Many tools have overlapping functionality across categories (e.g., multiple search_arxiv, search_google_scholar, real estate tools, DNS/WHOIS checks). An agent would struggle to differentiate between similar tools from different categories, leading to ambiguity.
Tools follow a 'category__verb_noun' pattern mostly, but verbs vary (get, search, screen, check, etc.) and some categories use different orders (e.g., 'get_repo_stats' vs 'search_repos'). The consistency is acceptable but not uniform across the entire set.
With 152 tools, the server is excessively large for a single MCP server. While it aims to be an all-in-one gateway, the sheer number overwhelms the agent and likely exceeds practical limits for coherent selection.
The server covers a wide range of domains (finance, real estate, news, developer tools, etc.) but has notable gaps (e.g., social media APIs, CRM tools). Coverage is broad but not exhaustive, and some niche areas (e.g., global stock exchanges) are over-represented.