Search the live web and return ranked title/url/snippet results, through an automatic multi-engine failover chain. (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 |
|---|---|---|---|
| query | Yes | Search query | |
| max_results | No | 1-25 (default 10) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the automatic multi-engine failover chain and notes that the tool is free, with a paid API alternative, adding context beyond the bare schema. However, with no annotations provided, it fails to mention rate limits, authentication needs, or error behavior, leaving significant transparency gaps.
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 first sentence is concise and front-loaded, clearly stating the tool's function. The second sentence is a promotional note about the paid API and directs to 'paid_catalogue'; while tangential, it adds useful cross-information, so it does not feel wasteful.
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?
For a simple two-parameter tool with no output schema, the description explains the result format (title/url/snippet) and ordering (ranked), which is sufficient. It omits potential failure modes or pagination details, but these are not critical for basic invocation, 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?
The input schema already describes both parameters with 100% coverage, so the description adds no parameter-specific detail. Per the rubric, the baseline 3 is appropriate when schema covers all parameters and the description doesn't compensate further.
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 uses a specific verb 'Search' and identifies the resource as 'the live web', with a clear output of 'ranked title/url/snippet results'. This differentiates it from the sibling data-lookup tools like 'air_quality' and 'geocode', which serve different purposes.
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 general live-web searches but does not explicitly state when to use this tool versus alternatives or mention any exclusions. The mention of the paid API is a cross-reference rather than usage guidance, so the guidance remains only implied.
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.