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Glama
kongyo2

Japanese Weather MCP Server

by kongyo2

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
get_weather_forecastA

Get weather forecast for a Japanese city using city ID

get_available_city_idsB

Get a list of available city IDs for Japanese cities

get_weather_by_city_nameB

Get weather forecast for common Japanese cities by name

Prompts

Interactive templates invoked by user choice

NameDescription
weather-forecastGenerate a weather forecast request

Resources

Contextual data attached and managed by the client

NameDescription
Weather API Documentation

TDQS

A3.5/5.0

Scored across 3 tools

Disambiguation3/5

The tools have some overlap in purpose, as both get_weather_by_city_name and get_weather_forecast retrieve weather forecasts, but they differ in input parameters (city name vs. city ID). The get_available_city_ids tool is distinct, providing city IDs. Descriptions help clarify the differences, but an agent might initially confuse the two weather tools.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case, starting with 'get_' for retrieval actions. The naming is predictable and readable, with no deviations in style or convention across the set.

Tool Count3/5

With only 3 tools, the server feels thin for a weather domain that typically includes more operations like historical data or alerts. However, it covers basic forecast retrieval and city ID listing, which is borderline but functional for minimal use cases.

Completeness3/5

The server provides core forecast retrieval and city ID listing, but there are notable gaps such as missing historical weather data, alerts, or multi-day forecast options. It covers basic needs but lacks comprehensive lifecycle coverage for a weather service domain.

Maintenance

ActivityInactive
ResponsivenessNo issues