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Find Nearby Weather Stations

meteostat.stations.nearby
Read-onlyIdempotent

Find Meteostat weather stations near a latitude/longitude coordinate, sorted by distance. Returns station IDs to use with station_info and the daily/monthly/hourly observation tools. Data: Meteostat open station directory (CC BY 4.0), no auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude of the search point (WGS84 decimal degrees).
lonYesLongitude of the search point (WGS84 decimal degrees).
limitNoMaximum number of stations to return, nearest first (default 10, max 50).
radius_kmNoSearch radius in kilometers (default 100, max 500).

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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds value beyond annotations by stating the output (station IDs), the sort order (by distance), the data source (Meteostat open directory), license (CC BY 4.0), and no auth requirement. No contradiction with 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?

Three sentences with zero redundancy. The main action and key output are front-loaded, followed by a data/attribution note. Every sentence earns its place.

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?

A read-only, idempotent lookup tool with a defined output schema. The description provides all necessary context: what it does, what it returns, how results are ordered, and data licensing/auth. Nothing critical is missing for an agent to call it 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 coverage is 100%, so all four parameters are documented with bounds and defaults. The description adds minimal extra meaning beyond the schema, only noting 'near a coordinate' and 'sorted by distance' which align with existing param descriptions. Baseline 3 is appropriate since the schema carries the load.

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 tool finds weather stations near a coordinate, sorted by distance, and returns station IDs. It explicitly names the intended downstream use with station_info and observation tools, which distinguishes it from those siblings. The purpose is specific and unambiguous.

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?

It provides clear context that the tool is for locating stations and tells the agent to use the returned IDs with other tools, but does not explicitly contrast with alternative nearby-station tools (e.g., brightsky.stations.nearby) or state when not to use it. Still, the downstream guidance is useful and implies when this tool is appropriate.

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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