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TypeScript
Remote

Aviation Weather — TAF Forecast

aviationweather.forecast.taf
Read-onlyIdempotent

Retrieve Terminal Aerodrome Forecasts for one or more ICAO airports, including decoded period-by-period wind, visibility, weather, and cloud forecasts plus the raw bulletin.

Instructions

Retrieve the Terminal Aerodrome Forecast (TAF) for one or more ICAO airport stations. A TAF covers a 24–30 hour window and includes time-bracketed forecast periods with expected wind, visibility, weather phenomena (rain, fog, snow), and cloud layers. Returns decoded period-by-period breakdown plus the raw TAF bulletin string. Issued every 6 hours from major airports. Source: NOAA Aviation Weather Center — US Government public domain, no auth required.

Input Schema

NameRequiredDescriptionDefault
idsYesComma-separated ICAO airport codes to retrieve Terminal Aerodrome Forecasts for (e.g. "KJFK", "KJFK,KLAX"). Most major airports publish a TAF valid 24–30 hours ahead.

Output Schema

NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool 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.

  1. Addedv2.2.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already provide readOnly, idempotent, and non-destructive hints. The description adds behavioral value by specifying the return format (decoded breakdown plus raw TAF string), update frequency (every 6 hours), and source/licensing (NOAA, public domain, no auth). This goes beyond the structured data.

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?

Four sentences with front-loaded action, followed by context, return details, and source. Each sentence contributes useful information; there is no redundant filler, though it could be tightened slightly.

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?

Given an output schema exists, the description sufficiently covers purpose, return format, update cadence, source, and access requirements. For a single-parameter read-only tool, this is nearly complete; only minor details like station limits or error conditions are absent.

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 coverage is 100% and the description does not add new meaning to the 'ids' parameter beyond restating 'one or more ICAO stations'. It mentions issuance frequency but not parameter-specific details, so it stays at the baseline for fully covered schemas.

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?

States a specific verb ('Retrieve') with a clear resource ('Terminal Aerodrome Forecast') and scope (ICAO stations). It explains the contents (time-bracketed periods, wind, visibility, weather, cloud layers) and distinguishes itself from current-condition tools by the 24–30 hour forecast window.

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 implies use for forecast data through the TAF definition but never explicitly names alternatives like aviationweather.observation.metar or states when not to use it. No exclusions or alternative routing, though the forecast/current distinction is implicit.

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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