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meteo-swiss-mcp

by cuolm

hourly_forecast

Get hour-by-hour weather for any Swiss location: temperature with likely range, rain chance, and conditions in words. Plan a specific hour or afternoon window up to eight days ahead.

Instructions

        Get the weather hour by hour for a location: temperature with its likely range, chance
        of rain and the weather in words.

        Use this for one hour, such as "how warm is it at 15:00", or part of a day, such as "how
        is the afternoon" or "when is the best time for a walk". Without end it returns the one
        hour starting at start. Each row covers the hour from its "from" to its "to": the
        temperature is the mean of that hour, while the rain chance and the weather cover the 3
        hours up to "to", as MeteoSwiss publishes them only per 3 hours. For whole days use
        daily_forecast, for rain amounts rain_outlook.

        Args:
            location (str): Location name (e.g., "Zurich") or Swiss postal code (e.g., "8001").
            start (str): Swiss local time in ISO 8601 without offset, e.g. "2026-09-23T15:00". Today or up to 8 days ahead.
            end (str): Optional. Swiss local time in ISO 8601 without offset, at most 24 hours after start.

        Returns:
            dict: The resolved location with its altitude, one row per hour (from, to,
                temperature in Celsius as its median and its 10th and 90th percentile, rain
                chance in percent, weather in words with a matching emoji), and the model run.
                In 8 of 10 possible outcomes, the temperature lies between the two percentiles.

        Examples:
            hourly_forecast("Zurich", "2026-09-23T15:00")                        # one hour
            hourly_forecast("Zurich", "2026-09-23T12:00", "2026-09-23T18:00")    # the afternoon
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
startYes
locationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

A5/5.0
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral details: the default single-hour return when end is omitted, the exact time semantics (from/to, 3-hour coverage for rain/weather per MeteoSwiss), and the percentile interpretation for temperature. This goes far beyond a generic summary.

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 structured with clear sections (description, args, returns, examples) and front-loads the purpose. Every sentence adds value, and the length is justified by the complexity of the data semantics. No redundancy or filler.

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?

Despite no output schema and no annotations, the description covers everything an agent needs to call the tool correctly: input formats, time bounds, return structure, and the meaning of the data fields. It even explains the 3-hour aggregation rationale. Nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description compensates completely: it specifies the location format (name or Swiss postal code), start format with example and valid range (today up to 8 days ahead), and end constraints (optional, at most 24 hours after start). Examples illustrate real calls.

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 opens with a specific verb+resource ('Get the weather hour by hour for a location') and enumerates the exact data delivered (temperature range, rain chance, weather in words). It also names the sibling tools it is not (daily_forecast, rain_outlook), so an agent can distinguish it immediately.

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?

Provides explicit use cases ('Use this for one hour... or part of a day') and gives concrete natural-language queries ('how is the afternoon'). It also states when to use alternatives ('For whole days use daily_forecast, for rain amounts rain_outlook'), leaving no ambiguity.

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