A
licenseNot graded
qualityD
maintenanceProvides weather alerts and forecasts for US locations using the National Weather Service API.
70 npm
GPL 3.0
Weather MCP Server
날씨 MCP 서버
National Weather Service (NWS) API를 사용하여 미국 날씨 정보를 제공하는 Model Context Protocol (MCP) 서버입니다. FastMCP로 구축되었습니다.
기능
이 서버는 AI 어시스턴트가 실시간 날씨 데이터를 가져올 수 있도록 다음과 같은 도구를 제공합니다:
get_alerts(state: str): 특정 미국 주(CA, NY, TX와 같은 2글자 주 코드 사용)에 대한 활성 날씨 경보를 가져옵니다. 이벤트, 심각도, 설명 및 안전 지침에 대한 세부 정보를 반환합니다.get_forecast(latitude: float, longitude: float): 특정 위치(위도 및 경도 사용)에 대한 상세 날씨 예보를 가져옵니다. 향후 5개 기간(예: 오늘 오후, 오늘 밤, 내일 등)에 대한 예보를 반환합니다.
Related MCP server: weather-mcp
사전 요구 사항
Python 3.10 이상
uv패키지 관리자
설치 및 설정
이 프로젝트는 의존성 관리를 위해 uv를 사용합니다. 설정 방법은 다음과 같습니다:
저장소 복제
의존성 설치 (uv를 사용하여 실행하면 가상 환경이 생성됩니다):
uv sync
사용법
MCP 클라이언트가 상호 작용하는 방식인 표준 입출력을 통해 MCP 서버를 수동으로 실행할 수 있습니다:
uv run weather.pyClaude Desktop과 통합
이 서버를 Claude Desktop과 함께 사용하려면 claude_desktop_config.json에 추가해야 합니다:
{
"mcpServers": {
"weather": {
"command": "uv",
"args": [
"--directory",
"path/to/your/mcp-server",
"run",
"weather.py"
]
}
}
}사용자 지정 MCP 클라이언트와 통합
사용자 지정 Python MCP 클라이언트가 있는 경우 다음과 같이 연결할 수 있습니다:
from mcp import StdioServerParameters
server_params = StdioServerParameters(
command="uv",
args=["--directory", "path/to/mcp-server", "run", "weather.py"],
env=None
)
# Pass server_params to your MCP client사용된 API
National Weather Service API (API 키 필요 없음)
Available Tools
2 toolsget_alertsA
Get weather alerts for a US state.
Args: state: Two-letter US state code (e.g. CA, NY)
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
A4.4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. 'Get' implies a read-only operation, but the description does not explicitly state side-effect-free behavior or any caveats about alert types or data source. It is not misleading, but it adds minimal behavioral context beyond what the name implies.
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 extremely concise, with a front-loaded purpose statement followed by a compact Args block. Every sentence earns its place and there is no filler.
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?
With a single well-documented parameter, an output schema, and no siblings, the description plus schema fully covers what an agent needs to invoke the tool correctly. No missing context for this simple operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description fully compensates by specifying the parameter format ('Two-letter US state code') and providing concrete examples ('CA, NY'). This adds real meaning beyond the raw schema type string.
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 states a specific verb ('Get'), a clear resource ('weather alerts'), and a clear scope ('US state'). It is unambiguous and leaves no doubt about what the tool does, even without siblings to differentiate from.
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?
There are no sibling tools, so explicit routing guidance is unnecessary. The description clearly implies usage: when you need weather alerts for a US state. It lacks explicit exclusions, but nothing is misleading or missing for a tool of this simplicity.
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.
Args: latitude: Latitude of the location longitude: Longitude of the location
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | ||
| longitude | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
C2.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must carry behavioral context. It only says 'get' a forecast and gives no indication of units, time range, coordinate format, or whether this is a read-only operation. Nothing contradicts annotations, but little is disclosed beyond the basic action.
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?
The description is short and the core purpose is front-loaded. The Args block is somewhat redundant with the schema but does not add significant bloat, keeping the overall entry compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides the essential call requirements (latitude and longitude) and the presence of an output schema reduces the need to document return values. However, it omits practical context like expected coordinate units, available forecast periods, and why an agent would choose this over get_alerts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The Args section repeats the parameter names with minimal glosses ('Latitude of the location'), adding almost no meaning beyond the schema titles. Since schema description coverage is 0%, the description should compensate with coordinate format or range details, but it does not.
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 uses a clear verb and resource: 'Get weather forecast for a location'. It does not explicitly mention the sibling get_alerts, but the forecast-vs-alerts distinction is clear enough from the domain.
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?
No guidance is given about when to use this tool instead of get_alerts, nor are any exclusions or alternative conditions provided. The intended usage is only implied by the tool name and description.
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.
2 tool updates
v0.1.0- First observed
get_alerts - First observed
get_forecast
TDQS
B3.4/5.0
Scored across 2 tools
Disambiguation5/5
get_alerts and get_forecast have clearly distinct purposes: one for weather alerts by state, the other for forecast by coordinates. No overlap exists.
Naming Consistency5/5
Both tools follow a consistent verb_noun pattern (get_alerts, get_forecast), making them predictable.
Tool Count3/5
With only 2 tools, the server feels thin for a weather domain, bordering on insufficient scope.
Completeness2/5
Common weather operations like current conditions, hourly forecast, or radar are missing, leaving significant gaps for typical use cases.
Maintenance
ActivityInactive
ResponsivenessNo issues
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Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceProvides US weather alerts and forecasts via the National Weather Service API.70 npmGPL 3.0
- AlicenseNot gradedqualityDmaintenanceProvides weather alerts and forecasts for US locations using the National Weather Service API.GPL 3.0
- AlicenseNot gradedqualityDmaintenanceProvides weather alerts and forecasts for US locations using the National Weather Service API.70 npmGPL 3.0