World Bank time series for a country: gdp, gdp_per_capita, population, inflation, unemployment, life_expectancy, co2_per_capita or internet_users. (Free. This server also sells a paid API — call paid_catalogue for the routes and prices; x402 over USDC on Base, no signup.)
| Name | Required | Description | Default |
|---|---|---|---|
| years | No | 1-60 most recent years (default 5) | |
| country | Yes | ISO 2- or 3-letter country code | |
| indicator | No | Alias above, or a World Bank code |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It adds context about being free and mentioning the paid API, which is useful. However, it does not disclose output format, rate limits, or behavior on invalid inputs, so transparency is incomplete.
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 concise, front-loaded with the core purpose in the first sentence. The second sentence about the paid API is relevant and adds context without being verbose. Every sentence earns its place.
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 params, no output schema), the description covers the essential information: what data is available and how to get it. It doesn't explain return structure, but that is not critical here. The paid API mention adds extra context, making it fairly complete.
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 100%, but the description adds value by listing the valid indicator aliases (gdp, population, etc.) that the schema only refers to as 'Alias above'. This goes beyond the schema's basic descriptions, aiding parameter interpretation.
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 explicitly states that the tool provides World Bank time series data for a country and lists specific indicators (gdp, gdp_per_capita, etc.). This clearly distinguishes it from sibling tools like air_quality or earthquakes, making the purpose specific and unambiguous.
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 retrieving country-level economic indicators. It also mentions the paid API and directs users to 'paid_catalogue' for paid routes, offering context for alternative/premium options. However, it does not explicitly state when to use this tool over sibling tools, so a slight gap remains.
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 clear, distinct purpose (air quality, country indicators, earthquakes, elevation, geocode, holidays, URL reading, web search, catalogue). The only overlap is that geocode already returns elevation, making the separate elevation tool redundant and potentially confusing.
All tool names follow a consistent lowercase snake_case pattern, mixing noun-based names (earthquakes, elevation) and verb_noun names (read_url, web_search). The style is uniform across the set, so naming is predictable and readable.
Nine tools is a reasonable count for a general-purpose data/web utility server. However, the set feels like a random assortment of free APIs rather than a coherent scoped collection, which slightly undermines the sense of appropriateness.
The server name 'tokenguard' implies a focus on token safety and blockchain intelligence, but the free tools cover unrelated domains (air quality, geocoding, holidays, web). The actual token-safety features are only mentioned in the paid_catalogue and are not exposed as MCP tools, leaving a significant gap between the server's apparent purpose and its actual capabilities.