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met-mcp

met-mcp

by trondbjoroy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Get weather forecast

get_forecast

Retrieve hourly weather forecasts for any latitude/longitude coordinate, with configurable forecast length up to 48 hours, using MET Norway's global data.

Instructions

Get an hourly weather forecast from MET Norway (Yr) for a coordinate. Works worldwide, best coverage in the Nordics.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "latitude": "<latitude>",
      "longitude": "<longitude>"
    },
    "name": "get_forecast"
  }
}

Input Schema

NameRequiredDescriptionDefault
hoursNoHow many hours ahead to include
latitudeYesLatitude in decimal degrees
longitudeYesLongitude in decimal degrees

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does state the data source and coverage limitations ('best coverage in the Nordics'), which is useful. However, it omits any mention of response format, potential errors, rate limits, or whether the forecast includes specific metrics (temperature, wind, etc.), leaving the agent to assume standard behavior.

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?

Two sentences with no superfluous content. The primary purpose and scope are front-loaded, and the coverage note is placed second. Every word adds value.

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?

For a simple read-only forecast tool with fully documented parameters, the description is nearly complete. It explains the source, scope, and the nature of the data (hourly forecast). The lack of an output schema and behavioral details (like units or error handling) is a minor gap given the low complexity, but the description is sufficient for an agent to understand the tool's core function.

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 input schema already provides clear descriptions for all three parameters ('latitude/longitude in decimal degrees', 'hours ahead to include'). The description adds the 'hourly' context which reinforces the `hours` parameter meaning, but adds little beyond that. With 100% schema coverage, a 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 clearly states the action ('Get'), the resource ('hourly weather forecast'), and the source ('MET Norway (Yr)') for a coordinate. It differentiates from sibling tools like get_nowcast (short-term) and get_historical_weather (past) by its explicit 'forecast' and 'hourly' scope. The global coverage hint adds further distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context ('Works worldwide, best coverage in the Nordics') that implies general forecast use, but it does not explicitly state when to use this tool vs alternatives like get_nowcast, get_weather_alerts, or get_sun_events. No exclusions or decision criteria are provided, so the agent must infer usage from the tool names alone.

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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