apibase

SMHI — Point Weather Forecast

smhi.weather.forecast

Read-onlyIdempotent

Get an 82-step hourly weather forecast (~10 days) for any point in Europe from the Swedish Meteorological and Hydrological Institute (SMHI). Uses SMHI's high-resolution NWP model (snow1g) covering most of Europe at ~2.5 km grid spacing. Each hourly step includes 25 parameters: air temperature (°C), wind speed (m/s), wind direction (°), wind gust (m/s), relative humidity (%), sea-level pressure (hPa), visibility (km), thunderstorm probability (%), cloud cover (%), precipitation amount (mm/h, with min/max/median), precipitation probability (%), frozen precipitation probability (%), symbol_code (WMO weather symbol 1–27). Swedish weather symbol codes: 1=clear sky, 2=nearly clear, 3=variable cloudiness, 4=half-cloudy, 5=cloudy, 6=overcast, 7=fog, 8=light rain, 9=moderate rain, 10=heavy rain, 11=thunderstorm, 12=light sleet, 13=moderate sleet, 14=heavy sleet, 15=light snow, 16=moderate snow, 17=heavy snow. No API key required — SMHI open data, Creative Commons BY 4.0.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`latitude`	Yes	Latitude in decimal degrees (WGS84). Covers most of Europe. Examples: 59.3293 = Stockholm, 57.7089 = Göteborg, 67.8558 = Umeå, 51.5074 = London.
`longitude`	Yes	Longitude in decimal degrees (WGS84). Covers most of Europe. Examples: 18.0686 = Stockholm, 11.9746 = Göteborg, 20.2253 = Umeå, -0.1278 = London.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`error`	No	Present only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
`result`	No	Tool 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.

First observedSep 22, 2026

TDQS

A4.4/5.0

Behavior5/5

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

The description goes far beyond the annotations by detailing the data source (SMHI high-resolution NWP model), grid spacing, all 25 parameters with units, and the complete WMO symbol code legend. It also discloses licensing and the no-API-key requirement, which are behavioral traits not captured in annotations. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every sentence serves a purpose: it front-loads the core purpose, then enumerates parameters and symbol codes, and ends with licensing. The symbol code list is extensive but necessary for interpreting results. It could be slightly trimmed, but it's not bloated with redundant content.

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?

Given the complexity of the output (25 parameters, symbol codes), the description is remarkably complete. It explains the forecast horizon, model, coverage, units, and licensing, leaving no significant gaps for an agent to call the tool correctly. The presence of an output schema reduces the need to describe return format, and the description covers everything else.

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?

The schema already provides thorough descriptions for latitude and longitude, including examples and range limits (100% coverage). The description repeats the coverage of Europe but adds no new parameter-specific semantics beyond what the schema provides. The baseline of 3 is appropriate given full schema coverage.

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's purpose: obtaining an 82-step hourly weather forecast for any point in Europe from SMHI. It specifies the verb (get), the resource (weather forecast), and the scope (point in Europe), making it distinct from other weather tools in the sibling list by naming the specific provider and model.

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 implies usage for forecasts, but it doesn't explicitly mention alternatives or when not to use it. It provides clear context about the forecast nature and geographical coverage, but it lacks explicit exclusions or references to sibling tools like observations or warnings.

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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