List the paid API routes this same server offers, with prices and which ones need no input. The MCP tools here are free and general-purpose; the paid routes are specialised (on-chain token safety, live DEX prices, wallet intel, supply-chain scans). Payment is x402 over USDC on Base — no account or API key. Takes no arguments.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses important behavioral traits: payment is via x402 over USDC on Base, no account or API key is needed, and the tool takes no arguments. It also clarifies that MCP tools are free. However, it does not explicitly state that this particular tool is read-only or whether it incurs a charge, though 'list' and 'free' imply it.
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 compact, front-loaded with the core action, and every sentence adds value. It efficiently covers purpose, differentiation, payment details, and parameter confirmation without irrelevant filler.
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 zero-parameter, no-output-schema catalogue tool, the description is complete. It tells the user what the tool lists (paid routes with prices and input requirements), who it is for (those needing specialised data), and how payment works. It also clarifies the relationship to the free MCP tools, providing enough context to invoke it 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 tool has zero parameters, and the schema is empty. The description explicitly confirms 'Takes no arguments', which removes any ambiguity. Since there are no parameters to document, the description fully compensates for the schema's emptiness.
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 verb 'List' and the resource 'the paid API routes this same server offers', with specific detail about prices and input requirements. It also distinguishes itself from the sibling free MCP tools by explaining that the paid routes are specialised for on-chain token safety, live DEX prices, wallet intel, and supply-chain scans.
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 provides clear context on when to use this tool: it is a catalogue of paid routes, while the MCP tools are free and general-purpose. It gives examples of specialised use cases but does not explicitly state 'when not to use' or name alternative tools by their tool names, so it falls short of a full explicit usage guide.
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 serve clearly distinct purposes: air quality, skill audit, country data, earthquakes, elevation, geocoding, holidays, URL reading, and web search. However, `audit_skill_text` and `audit_skill_url` both audit for malicious behavior, differing only in input type, which could cause slight confusion.
Tool names use a mix of snake_case and descriptive phrases without a strict verb_noun pattern. Some names are verbs (e.g., `geocode`, `audit_skill_text`, `read_url`), while others are nouns (e.g., `air_quality`, `earthquakes`). The naming is readable but inconsistent in style.
With 11 tools, the count is well-scoped for a server that aggregates diverse free data and security services. Each tool serves a distinct and useful function, and the `paid_catalogue` tool properly manages the paid extension without bloating the main set.
The tool set covers a broad range of data types (environment, economic, geographic, security), but for each individual domain, coverage is shallow. For example, only current air quality is provided (no historical data), and skill auditing only returns a scan result (no detailed remediation). The set lacks update, delete, or drill-down operations per domain.