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akaramanapp

Weather MCP Server

by akaramanapp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

날씨 MCP 서버

미국 기상청(NWS) API를 사용하여 미국 지역의 날씨 정보와 경보를 제공하는 모델 컨텍스트 프로토콜(MCP) 서버입니다. 이 서버는 모델 컨텍스트 프로토콜을 통해 AI 에이전트가 사용하도록 설계되었습니다.

특징

  • 미국 모든 주의 날씨 알림을 받을 수 있는 도구

  • 좌표를 사용하여 미국 내 모든 지역의 자세한 날씨 예보를 얻는 도구

  • 온도, 바람 상태 및 간단한 예보 설명을 지원합니다.

  • 국립 기상청의 실시간 데이터

Related MCP server: Weather MCP Server

필수 조건

  • Node.js(v16 이상)

  • npm 또는 yarn 패키지 관리자

설치

  1. 저장소를 복제합니다.

지엑스피1

  1. 종속성 설치:

npm install

  1. 애플리케이션을 빌드하세요:

npm run build

MCP 도구

서버는 AI 에이전트가 사용할 수 있는 두 가지 MCP 도구를 제공합니다.

알림 받기

특정 미국 주의 날씨 알림을 받으세요.

매개변수:

  • state : 두 글자 주 코드(예: CA, NY)

응답 예시:

{
  "content": [
    {
      "type": "text",
      "text": "Active alerts for CA: ..."
    }
  ]
}

예측 얻기

좌표를 사용하여 특정 위치의 날씨를 예보합니다.

매개변수:

  • latitude : 위치의 위도(-90~90)

  • longitude : 위치의 경도(-180 ~ 180)

응답 예시:

{
  "content": [
    {
      "type": "text",
      "text": "Morning: Temperature: 72°F, Wind: 5mph NW, Partly cloudy..."
    }
  ]
}

프로젝트 구조

weather/
├── src/
│   └── index.ts    # Main server code with MCP tool implementations
├── build/          # Compiled JavaScript files
├── package.json    # Project dependencies and scripts
└── tsconfig.json   # TypeScript configuration

기술적 세부 사항

  • TypeScript로 구축됨

  • MCP(Model Context Protocol) 서버를 구현합니다.

  • MCP 서버 구현을 위해 @modelcontextprotocol/sdk를 사용합니다.

  • 국립 기상청(NWS) API와의 인터페이스

  • Node16 모듈 해상도를 갖춘 ES2022 타겟

개발

서버를 수정하거나 확장하려면:

  1. src/index.ts 파일을 변경하세요

  2. 애플리케이션을 다시 빌드합니다.

npm run build

종속성

  • @modelcontextprotocol/sdk: MCP 서버 구현 프레임워크

  • zod: 도구 매개변수에 대한 런타임 유형 검사 및 검증

  • TypeScript: 유형 안전을 위한 개발 종속성

특허

아이에스씨

노트

  • 이 서버는 National Weather Service API를 사용하므로 미국 지역에서만 작동합니다.

  • API 요청은 속도 제한이 있으며 User-Agent 헤더가 필요합니다.

  • 모든 좌표는 십진수 형식이어야 합니다.

  • 이는 독립형 CLI 애플리케이션이 아니라 모델 컨텍스트 프로토콜을 통해 AI 에이전트에 도구를 제공하는 서버입니다.

Available Tools

2 tools
get-alertsC

Get weather alerts for a state

ParametersJSON Schema
NameRequiredDescriptionDefault
stateYesTwo-letter state code (e.g. CA, NY)

TDQS

C2.9/5.0
Behavior2/5

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 states what the tool does but doesn't describe traits like rate limits, authentication needs, error handling, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its 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?

The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core purpose without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns complex alert data. It doesn't explain what the alerts include, how they're formatted, or any limitations, leaving the agent with insufficient context for effective use.

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 description doesn't add any parameter-specific information beyond what's in the input schema, which has 100% coverage and fully documents the 'state' parameter. This meets the baseline score of 3, as the schema adequately handles parameter semantics without needing extra description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('weather alerts for a state'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from its sibling tool 'get-forecast', which likely provides different weather data, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus its sibling 'get-forecast' or any alternatives. It lacks context about usage scenarios, exclusions, or prerequisites, offering only a basic statement of function.

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

get-forecastC

Get weather forecast for a location

ParametersJSON Schema
NameRequiredDescriptionDefault
latitudeYesLatitude of the location
longitudeYesLongitude of the location

TDQS

C2.9/5.0
Behavior2/5

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 states what the tool does but doesn't describe any behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, or what the response format might be. This is inadequate for a tool with zero annotation coverage.

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?

The description is a single, clear sentence that efficiently conveys the core purpose without any unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that there are no annotations and no output schema, the description is incomplete. It doesn't provide enough context about behavioral aspects, response format, or how this tool differs from its sibling. For a tool with this level of complexity and lack of structured data, the description should do more to compensate.

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 description coverage is 100%, with both parameters (latitude and longitude) well-documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema, so it meets the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('weather forecast for a location'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'get-alerts', which likely provides different weather-related information, so it doesn't achieve the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling 'get-alerts' or explain the difference between getting a forecast versus alerts, leaving the agent without context for tool selection.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updates
    • First observedget-alerts
    • First observedget-forecast
Deploy Server
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TDQS

B3.1/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: get-alerts retrieves weather alerts for a state, while get-forecast provides weather forecasts for a location. There is no overlap in functionality, and an agent can easily differentiate between them based on their specific use cases.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern with hyphens (get-alerts and get-forecast). This uniformity makes the tool set predictable and easy to understand, with no deviations in style or convention.

Tool Count2/5

With only two tools, the server feels thin for a weather domain, as it lacks essential operations like getting current conditions, historical data, or radar information. While the tools are well-defined, the count is too low to provide comprehensive coverage for typical weather-related tasks.

Completeness2/5

The tool set is severely incomplete for a weather server, missing core functionalities such as current weather, historical data, and radar or satellite imagery. Agents will face significant gaps when trying to perform common weather queries, leading to potential failures in broader tasks.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • MCP Weather Server

    adarshem
    A
    license
    B
    quality
    F
    maintenance
    A Model Context Protocol server that provides tools to fetch weather alerts for US states and forecasts based on latitude/longitude coordinates using the US National Weather Service API.
    2
    159 npm
    1
    MIT

  • Weather MCP Server

    mauricioTechDev
    A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol server that enables AI models to fetch weather alerts and detailed forecasts for US locations using the National Weather Service API.
    159 npm
    GPL 3.0

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