Skip to main content
Glama

MGM hava durumu (şu an + 5 günlük tahmin)

mgm_hava_durumu
Read-only

Retrieve current weather conditions and 5-day forecast for any Turkish province or district, including temperature, humidity, wind, and pressure, from the state meteorological service.

Instructions

Meteoroloji Genel Müdürlüğü'nden bir il ya da ilçe için anlık gözlem (sıcaklık, hissedilen, nem, rüzgâr, basınç, hadise) ve 5 günlük tahmin (günlük en düşük/en yüksek, hadise, rüzgâr). Current conditions and 5-day forecast for a Turkish province or district from the state meteorological service. İlçe verilmezse il merkezi.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ilYesİl adı, örn. İstanbul
ilceNoİlçe adı, örn. Kadıköy (isteğe bağlı)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
veriYes
alindiYes
kaynakYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate readOnly and open-world behavior, lowering the bar. The description adds useful behavioral context beyond annotations: the authoritative source (MGM), the distinction between current observations and 5-day forecast, the specific metrics returned, and the fallback to province center when district is omitted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is compact and front-loaded with source and scope, but it duplicates the same information in Turkish and English, which adds redundancy. Also, the key fallback behavior ('İlçe verilmezse il merkezi') appears only in Turkish, so an English-only agent may miss it.

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 only two simple parameters)Skip this tool is simple and the output schema exists, the description is complete: it states data source, coverage window, included observation/forecast fields, and the district-omission fallback. No critical calling information is missing.

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

Parameters4/5

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

Schema coverage is 100% and both parameters already have example-rich descriptions Shema describes 'il' and 'ilce' adequately. The description adds the important default behavior that omitting ilce returns the province center, which is not stated in the schema, going beyond the baseline.

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 identifies the resource (MGM weather data) and the exact scope: current observations and 5-day forecast for a Turkish province or district. It enumerates the returned fields (temperature, feels-like, humidity, wind, pressure, event) and is easily distinguished from all non-weather sibling tools.

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 gives clear context on when to use the tool: for Turkish administrative locations and weather data from MGM. It also explains the default behavior when no district is provided ('İlçe verilmezse il merkezi'). No explicit alternatives are named, but no weather sibling exists, so the context is sufficient without exclusions.

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