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Historical climate records from the nearest AEMET climatological station

get_climate_history

Retrieve historical weather observations (temperature, precipitation, wind, humidity, sunshine) for any Spanish location, with daily records or long-term monthly averages.

Instructions

Finds the AEMET climatological station closest to the requested location and returns its measured history. mode='range' returns daily records (temperature, precipitation, wind, humidity, sunshine) between two dates; AEMET serves at most 6 months (186 days) per call, so longer histories need several calls. Ranges longer than 31 days are condensed into one line per month (mean max/min, total precipitation, rainy days, extremes) instead of one line per day. mode='normals' returns the station's long-term monthly averages. Use this for past weather and climate questions, not for forecasts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date as YYYY-MM-DD. Defaults to today when mode='range'.
fromNoStart date as YYYY-MM-DD. Required when mode='range'.
modeNo'range' (default) returns observed daily records between `from` and `to`. 'normals' returns the station's long-term monthly averages and ignores the dates.
locationYesWhere to look. Accepts a Spanish municipality name ('Madrid'), 5-digit INE code ('28079'), or a decimal coordinate pair ('40.4168,-3.7038').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden. It discloses the 6-month/186-day limit per AEMET call, the need for multiple calls for longer histories, and the 31-day threshold that changes output granularity, plus the fields returned in each mode. This is rich behavioral context beyond the schema.

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?

Four sentences, each earning its place: core purpose, mode behavior with limits, alternative mode, and use-case routing. It is front-loaded with the action and resource, then organized by mode. No fluff or redundant schema repetition.

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?

Given no output schema and no annotations, the description covers the key operational details: location resolution, mode parameters, date restrictions, output granularity, and outcome. An agent has enough to call the tool correctly and to plan pagination for long histories.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value by connecting mode to from/to behavior (dates only matter in 'range', normals ignores them), warning about condensation beyond 31 days, and prompting multi-call splitting beyond 186 days. It doesn't fundamentally add syntax, but the cross-parameter behavior is helpful.

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 states the tool finds the nearest AEMET climatological station and returns its measured history, which clearly distinguishes it from forecast and observation siblings. It also names the two modes of history, making the purpose unmistakable.

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

Usage Guidelines5/5

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

It explicitly says 'Use this for past weather and climate questions, not for forecasts,' giving both when-to-use and when-not-to-use guidance. The mode descriptions further tell the agent when to request a date range versus normals, so the tool is routed correctly without inspecting the schema.

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