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Meteostat

by io.github.pipeworx-io
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Find Stations

find_stations
Read-onlyIdempotent

Find Meteostat weather station IDs by place name and/or geographic proximity — the lookup you need BEFORE get_daily_history / get_monthly_normals (which require a station_id). Search by name ("San Francisco", "Heathrow"), filter by country (ISO-2 like "US", "GB"), and/or rank by nearest to a lat/lon. Returns each station's id, name, country, region, coordinates, elevation, timezone, and data inventory (which granularities — hourly/daily/monthly — are available and their date ranges, so you can pick a station that actually has the period you need). Use for "weather station near X", "what is the station ID for Y", "stations in country Z".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax stations to return (1-50, default 10).
queryNoStation/place name substring (case-insensitive), e.g. "Heathrow", "San Francisco".
countryNoISO-2 country code filter (e.g. "US", "GB", "DE").
near_latNoLatitude to rank stations by proximity (pair with near_lon).
near_lonNoLongitude to rank stations by proximity (pair with near_lat).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "country": "US",
+    "query": "San Francisco"
+  },
+  {
+    "limit": 5,
+    "near_lat": 51.4775,
+    "near_lon": -0.4614,
+    "query": "Heathrow"
+  }
+]
  2. Added
  3. Removed
  4. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe, idempotent lookup. The description adds behavioral details beyond annotations, such as returning data inventory with date ranges and the ability to rank by proximity. 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?

The description is concise yet comprehensive. It front-loads the core purpose in the first sentence, then provides essential context (prerequisite, examples, return data) in a well-structured flow. No redundant or unnecessary sentences; every sentence adds value.

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?

The description fully covers what an agent needs: the tool's role (station lookup before data tools), input semantics (name, country, coordinates), and output details (id, name, inventory with date ranges). There is no output schema, so the description compensates by listing return fields. All 5 optional parameters are addressed with examples.

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 input schema already documents all 5 parameters. The description adds value by explaining how parameters combine (e.g., 'pair near_lat with near_lon') and providing usage examples inline. It clarifies the purpose of each parameter beyond the schema descriptions (e.g., 'filter by country ISO-2').

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 station IDs by place name or geographic proximity. It uses specific verbs ('Find', 'lookup') and resources ('Meteostat weather station IDs'). It differentiates from siblings by explicitly naming it as the prerequisite for get_daily_history and get_monthly_normals, which are listed among sibling tools.

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 explicitly says 'the lookup you need BEFORE' specific data tools, providing when to use it. It gives concrete examples of queries (by name, country, proximity). It does not explicitly state when not to use it or list alternatives, but the context strongly implies it is for station discovery, not data retrieval.

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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