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Social Aemet Spain Weather

social_aemet_spain_weather
Read-only

Spanish weather station observations from AEMET OpenData (official): latest hourly readings (temperature, humidity, wind, pressure, precipitation…) for all stations or one station ID (idema, e.g. 3195 Madrid Retiro), as published by AEMET. Requires the operator's free AEMET OpenData key. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows, 1 to 500 (default 100)
stationNoAEMET station ID (idema), e.g. 3195; empty = all stations

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
sourceNo
stationNo
checkedAtNo
observationsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

The annotations already cover safety with readOnlyHint=true and openWorldHint=true. The description adds important non-schema behavior: authentication via an operator-provided AEMET OpenData key, a $0.002 USDC charge per successful call via x402, and no charge for failed calls.

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

Conciseness5/5

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

The description is front-loaded with the data source and payload, then follows with authentication and billing details. Every sentence earns its place and there is no redundant filler.

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?

With an output schema present, the description need not explain return values. It covers source, scope, station targeting, authentication, and billing, which is sufficient 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.

Parameters3/5

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

Schema description coverage is 100%, so both parameters are already documented in the schema. The description reinforces the station parameter with an example (Madrid Retiro) and explains the all-stations option, but it adds little beyond what the schema provides and does not mention the limit parameter.

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?

The description names a specific resource (Spanish weather station observations from AEMET OpenData) and a specific payload (latest hourly readings of temperature, humidity, wind, pressure, precipitation), with clear scope for all stations or a single idema. An agent can identify exactly what data this tool returns without opening the schema.

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?

The description makes the usage context clear: it returns latest hourly observations, can target all stations or one station ID, and requires an AEMET OpenData key plus per-call payment. It does not name alternatives, but no sibling weather tool exists in the provided list, so the lack of explicit exclusions is minor.

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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