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Get Daily Weather Observations

meteostat.observations.daily
Read-onlyIdempotent

Get a full calendar year of daily weather observations (temperature, precipitation, wind, pressure, sunshine, cloud cover) for a Meteostat weather station. Station ID comes from meteostat.stations_nearby. Data: Meteostat, aggregated from national weather services (CC BY 4.0), no auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesCalendar year to fetch daily observations for (e.g. 2024).
station_idYesMeteostat weather station ID, obtained from meteostat.stations_nearby.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful context beyond annotations: it specifies the data fields returned, the period (full year), the data source (Meteostat, CC BY 4.0), and that no auth is required. However, it does not disclose potential limitations like data coverage gaps or output size, which are not essential given the annotations.

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 two sentences with no filler. The first sentence front-loads the purpose and scope, listing the variables and the prerequisite. The second sentence covers data source, licensing, and auth requirements. Every sentence earns its place, and it is appropriately sized.

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

Completeness4/5

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

Given the output schema exists (covering return values), the description is contextual. It states the exact granularity, period, variables, and station ID prerequisite, and clarifies data provenance and auth. It does not explicitly mention alternatives or edge cases like data availability, but for a simple 2-param read tool, it is sufficiently complete.

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 covers 100% of both parameters, with year described as 'Calendar year to fetch daily observations for' and station_id described as 'Meteostat weather station ID, obtained from meteostat.stations_nearby'. The tool description reinforces this by mentioning 'full calendar year' and 'Station ID comes from meteostat.stations_nearby', but it adds minimal new meaning beyond the schema.

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 clearly states the action (Get), the resource (daily weather observations), and the scope (full calendar year), listing the measured variables (temperature, precipitation, wind, pressure, sunshine, cloud cover). It distinguishes itself from siblings like hourly and monthly by specifying 'daily' and 'full calendar year', and it also mentions the prerequisite station ID source.

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 provides clear context: it is for daily observations over a full calendar year, and it explicitly states that the station ID comes from meteostat.stations_nearby, which is a prerequisite. It does not explicitly compare to hourly/monthly siblings, but the granularity specification implies when to use this tool.

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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