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TimLukaHorstmann

MCP Weather

by TimLukaHorstmann
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TypeScript
Remote

Servidor meteorológico MCP

versión npm licencia versión del nodo asuntos descargas semanales

Un servidor de Protocolo de Contexto de Modelo (MCP) que proporciona pronósticos meteorológicos diarios y por hora mediante la API de AccuWeather.

Inicio rápido

Necesita una clave API de AccuWeather (nivel gratuito disponible).
Regístrate aquí y crea una aplicación para obtener tu clave.

Exporte su clave API como una variable de entorno:

export ACCUWEATHER_API_KEY=your_api_key_here

Luego ejecute el servidor meteorológico MCP directamente con:

npx -y @timlukahorstmann/mcp-weather

O bien, para acceso HTTP/REST a través de supergateway :

npx -y supergateway --stdio "npx -y @timlukahorstmann/mcp-weather" \
  --port 4004 \
  --baseUrl http://127.0.0.1:4004 \
  --ssePath /messages \
  --messagePath /message \
  --cors "*" \
  --env ACCUWEATHER_API_KEY="$ACCUWEATHER_API_KEY"

Related MCP server: Weather MCP Server

Ejemplo de configuración del servidor MCP

Para la integración con Claude Desktop u otros clientes compatibles con MCP, agregue esto a su configuración (por ejemplo, claude_desktop_config.json ):

{
  "mcpServers": {
    "weather": {
      "command": "npx",
      "args": ["-y", "@timlukahorstmann/mcp-weather"],
      "env": {
        "ACCUWEATHER_API_KEY": "your_api_key_here"
      }
    }
  }
}

Descripción general

Este servidor MCP permite que modelos lingüísticos de gran tamaño (como Claude) accedan a datos meteorológicos en tiempo real. Al integrarse con un LLM, permite al modelo:

  • Obtenga pronósticos meteorológicos precisos y actualizados

  • Proporcionar datos meteorológicos por hora para las próximas 12 horas.

  • Acceda a pronósticos meteorológicos diarios de hasta 15 días

  • Muestra datos en unidades métricas (°C) e imperiales (°F)

  • Ver información sobre temperatura, condiciones, precipitaciones y otros detalles meteorológicos.

Prerrequisitos

  • Node.js ≥18

  • Una clave API de AccuWeather (configurada a través de .env o su shell)

Configuración

  1. Clonar este repositorio:

    git clone https://github.com/TimLukaHorstmann/mcp-weather.git
cd mcp-weather

  2. Instalar dependencias:

    npm install

  3. Obtenga una clave API de AccuWeather:

  4. Crea un archivo .env con tu clave API:

    ACCUWEATHER_API_KEY=your_api_key_here

  5. Construir el proyecto:

    npm run build

Uso con Claude Desktop

  1. Configurar Claude Desktop para utilizar este servidor MCP:

    • Abra Claude Desktop

    • Vaya a Configuración > Desarrollador > Editar configuración

    • Agregue lo siguiente a su claude_desktop_config.json :

    {
  "mcpServers": {
    "weather": {
      "command": "npx",
      "args": ["-y", "@timlukahorstmann/mcp-weather"],
      "env": {
        "ACCUWEATHER_API_KEY": "your_api_key_here"
      }
    }
  }
}

  2. Reiniciar Claude Desktop

  3. En una nueva conversación, habilite el servidor MCP haciendo clic en el ícono del enchufe y seleccionando "clima".

  4. Ahora puedes pedirle a Claude pronósticos del tiempo como:

    • "¿Cuál es el pronóstico del tiempo por horas para la ciudad de Nueva York?"

    • "Dame el pronóstico de cinco días para Londres."

    • "¿Cómo estará el tiempo en Tokio esta semana en Fahrenheit?"

    • "¿Lloverá mañana en San Francisco?"

Herramientas disponibles

Pronóstico del tiempo por hora

  • Nombre de la herramienta: weather-get_hourly

  • Proporciona pronósticos por hora para las próximas 12 horas.

  • Parámetros:

    • sessionId (obligatorio): identificador único para la sesión

    • location (obligatorio): Ciudad o nombre de la ubicación

    • units (opcionales): "métricas" (Celsius, predeterminadas) o "imperiales" (Fahrenheit)

Pronóstico del tiempo diario

  • Nombre de la herramienta: weather-get_daily

  • Proporciona pronósticos diarios de hasta 15 días.

  • Parámetros:

    • sessionId (obligatorio): identificador único para la sesión

    • location (obligatorio): Ciudad o nombre de la ubicación

    • days (opcional): Número de días de pronóstico (1, 5, 10 o 15; el valor predeterminado es 5)

    • units (opcionales): "métricas" (Celsius, predeterminadas) o "imperiales" (Fahrenheit)

Desarrollo

  • Instalar dependencias de desarrollo: npm install

  • Limpie su código: npm run lint

  • Construir: npm run build

  • Ejecutar pruebas: npm test

  • Iniciar en modo de desarrollo: npm run dev

Contribuyendo

¡Agradecemos sus contribuciones! No dude en enviar una solicitud de incorporación de cambios.

Mejoras futuras

Siempre buscamos mejorar el Servidor Meteorológico MCP. Estas son algunas de las características que estamos considerando para futuras versiones:

  • Pronósticos horarios extendidos: más allá de 12 horas, por ejemplo, 24 o 48 horas.

  • Alertas meteorológicas: integración con la API de alertas meteorológicas severas de AccuWeather.

  • Autocompletar ubicación: búsqueda de ubicación mejorada con sugerencias de autocompletar.

  • Datos meteorológicos históricos: acceso a condiciones climáticas pasadas.

Si tienes ideas para otras funciones, ¡no dudes en abrir un problema!

Licencia

Este proyecto está licenciado bajo la licencia MIT: consulte el archivo de LICENCIA para obtener más detalles.

Available Tools

2 tools
weather-get_dailyA

Get daily weather forecast for up to 15 days

ParametersJSON Schema
NameRequiredDescriptionDefault
locationYesThe city or location for which to retrieve the weather forecast.
daysNoNumber of days to forecast (1, 5, 10, or 15). Default is 5.
unitsNoTemperature unit system (metric for Celsius, imperial for Fahrenheit). Default is metric.

TDQS

A3.8/5.0
Behavior3/5

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

There are no annotations, so the description carries the behavioral transparency burden. It communicates a read-only forecast lookup via 'Get' and adds the 15-day maximum, but it does not disclose response shape, potential errors, timezone behavior, or whether any authentication is needed. For a simple read operation this is acceptable but not thorough.

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 sentence with no wasted words. It front-loads the verb and resource and immediately gives the key constraint of 15 days.

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?

For a simple weather lookup with three fully documented parameters, the description is largely complete and an agent can invoke the tool correctly. The only notable gap is that there is no output schema and the description does not hint at the shape of the returned forecast payload.

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 description coverage is 100%: location, days, and units are all clearly documented in the input schema. The description adds no additional parameter meaning, which is acceptable because the structured schema already handles the documentation fully.

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 explicitly states the action ('Get'), the resource ('daily weather forecast'), and the scope ('up to 15 days'). This clearly distinguishes it from the sibling tool weather-get_hourly without requiring any additional inference.

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 word 'daily' and the tool name imply that this is for day-level forecasts rather than hourly ones, which is useful context. However, the description does not explicitly state when to use this tool versus weather-get_hourly or provide any exclusion criteria.

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

weather-get_hourlyA

Get hourly weather forecast for the next 12 hours

ParametersJSON Schema
NameRequiredDescriptionDefault
locationYesThe city or location for which to retrieve the weather forecast.
unitsNoTemperature unit system (metric for Celsius, imperial for Fahrenheit). Default is metric.

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It states the scope (hourly, next 12 hours) and implies a read-only operation, but does not mention return format, error behavior, or data source limitations. It is adequate but not rich.

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 concise sentence with no filler. It front-loads the core action and scope, making it easy for an agent to process quickly.

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?

For a simple two-parameter tool, the description is largely complete: it states the forecast type, granularity, and time window. It does not describe the return payload, but no output schema exists and the tool's purpose is straightforward enough that an agent can infer expected weather data fields.

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 description coverage is 100%, so both parameters are already documented in the schema. The description adds no additional parameter-level details beyond what the schema provides, so the baseline score of 3 applies.

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 uses a specific verb ('Get') and resource ('hourly weather forecast') with a clear time bound ('next 12 hours'). This clearly distinguishes it from the sibling tool weather-get_daily, which is for daily forecasts.

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 time range and 'hourly' granularity imply when to use this tool, but the description never explicitly names the alternative or states when to choose it instead. The guidance is present by inference, not direct instruction.

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 observedweather-get_daily
    • First observedweather-get_hourly
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.2/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: one provides daily forecasts for up to 15 days, while the other provides hourly forecasts for the next 12 hours. There is no overlap in functionality, and an agent can easily differentiate between them based on the time granularity and forecast duration.

Naming Consistency5/5

Both tools follow a consistent naming pattern with a prefix 'weather-' followed by a verb_noun structure (get_daily, get_hourly). This pattern is predictable and enhances readability, making it easy for agents to understand the tool's purpose at a glance.

Tool Count2/5

With only 2 tools, the server feels under-scoped for a weather domain. While the tools cover forecast retrieval, there are obvious gaps such as current weather conditions, historical data, or location-based searches, making the set too thin for comprehensive weather-related tasks.

Completeness2/5

The tool surface is severely incomplete for a weather server. It lacks essential operations like getting current weather, searching locations, or accessing historical data, which are core to weather applications. Agents will face dead ends when trying to perform basic weather queries beyond forecasts.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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