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clarehancock

Open-Meteo MCP Server

by clarehancock

get_weather_forecast

Fetch multi-day weather forecasts (up to 16 days) for any latitude/longitude, with daily summaries by default and optional hourly detail.

Instructions

Get a multi-day hourly and/or daily weather forecast (up to 16 days) for a specific latitude/longitude. Use geocode_location first if you only have a place name. Defaults to a useful set of daily summary variables; pass include_hourly=true for hour-by-hour detail as well.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latitudeYesLatitude in decimal degrees
timezoneNoTimezone for returned timestamps, e.g. 'America/New_York' or 'auto' to infer from coordinatesauto
longitudeYesLongitude in decimal degrees
forecast_daysNoNumber of forecast days to return (1-16, default 7)
include_hourlyNoWhether to also include hourly detail (default: daily summary only)
wind_speed_unitNoUnit for wind speed valueskmh
temperature_unitNoUnit for temperature valuescelsius
Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It explains the default behavior (daily summary variables), how to opt into hourly detail, the 16-day limit, and the prerequisite of having coordinates. It does not mention error conditions, rate limits, or exact return contents, but for a read-only forecast fetch the core behavior is transparent.

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 concise sentences front-load the core purpose, then add routing guidance and default behavior. Every sentence earns its place without unnecessary detail or repetition.

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?

The description is complete enough for a straightforward forecast tool: it covers purpose, coordinate requirement, geocoding prerequisite, forecast length, granularity, and default behavior. There is no output schema, and the 'useful set of daily summary variables' is not enumerated, but the core invocation context is well covered.

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 the schema already documents all parameters well. The description adds meaningful context for include_hourly and the 16-day maximum, but it does not substantially enhance the parameter semantics beyond what the schema provides, so the baseline of 3 is appropriate.

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 a specific verb-resource pair ('Get a multi-day ... weather forecast') with explicit scope (latitude/longitude, up to 16 days). It clearly distinguishes this from the sibling tools by emphasizing multi-day forecast versus geocoding or current weather.

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 explicitly instructs to use geocode_location first when only a place name is available, which is strong routing guidance. It does not explicitly contrast with get_current_weather, but 'multi-day forecast' versus 'current weather' is a clear implied distinction. Lacks an explicit when-not-to-use statement.

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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