Fetch a URL and return its main content as clean Markdown, boilerplate stripped. (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 |
|---|---|---|---|
| url | Yes | Page to fetch |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and sufficiently discloses that it returns clean Markdown stripped of boilerplate, and that the service is free. It does not mention potential limitations (e.g., dynamic content, paywalls, timeouts) or response error formats, which leaves some gaps, but the core output behavior is clearly stated.
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, with the primary purpose front-loaded in the first sentence. The second sentence about the paid API is somewhat tangential to the tool's core function but is short and provides relevant context about the service's broader ecosystem, so it does not significantly detract from conciseness.
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 tool with one parameter and no output schema, the description fully explains what the tool does, what it returns (clean Markdown), and the cost model. The absence of an output schema is compensated by explicitly stating the return format, making the description adequate for an agent to invoke the tool correctly.
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 documents the only parameter ('url' as 'Page to fetch'), so schema coverage is 100%. The description does not add additional meaning about URL formats, accepted protocols, or constraints, providing no extra value beyond the schema.
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 ('Fetch') and names the resource ('a URL') and the exact outcome ('return its main content as clean Markdown, boilerplate stripped'). This clearly distinguishes it from the sibling web_search tool, which searches rather than fetches a specific URL.
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 the tool is for fetching a specific URL, which contrasts with web_search but does not explicitly state when to choose one over the other. There is no when-not-to-use guidance or mention of alternatives beyond the paid API aside, which is more about monetization than usage 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.
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.