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Active tropical cyclones from the US National Hurricane

realestate_nhc_current_storms_v2
Read-only

Active tropical cyclones from the US National Hurricane Center (NOAA) CurrentStorms.json feed: name, id, classification, intensity (knots), pressure (mb), position, movement and the latest public advisory link. Empty list when no storm is active. Not a real-estate dataset. Related tools on this server, for a different need: realestate_iss_current_location when you need live position of the International Space Station. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "realestate_nhc_current_storms_v2"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
countNo
sourceNo
stormsNo
checkedAtNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint/openWorldHint annotations, it discloses the empty-result behavior ('Empty list when no storm is active'), the payment model ($0.002 USDC per successful call via x402 on Base, Solana or Arc), and that failed calls are not charged. Cost and billing semantics are exactly the kind of context annotations cannot convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose and field list, then disambiguation, then pricing. It is dense but well ordered; the ISS sibling mention is somewhat tangential padding, though it does serve the 'not real estate' clarification.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter read tool with an output schema, this is complete: it characterizes the source feed, the empty-state, the disambiguation from siblings, and the payment requirement. An agent has everything needed to decide to call it and to anticipate the cost.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so the baseline is 4. The description correctly doesn't invent parameter guidance and instead spends its words on output fields and billing, which is the right allocation of space.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and verb-level scope: active tropical cyclones from the NOAA NHC CurrentStorms.json feed, and enumerates the returned fields (name, id, classification, intensity, pressure, position, movement, advisory link). It also disambiguates from the odd 'realestate_' prefix by saying 'Not a real-estate dataset,' so an agent won't confuse it with the property siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context for use (current active storms, empty list when none) and explicitly routes the agent away to realestate_iss_current_location for a different need. It stops short of full when/when-not guidance — e.g., no mention of historical storms or alternative weather sources — but the intended use is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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