mcp-server-tempest 0.3.1

MCP Server for Retrieving Tempest Weather Data

WeatherFlow Tempest MCP Server

A Model Context Protocol (MCP) server that provides seamless access to WeatherFlow Tempest weather station data. This server enables AI assistants and applications to retrieve real-time weather observations, forecasts, and station metadata.

🌤️ Features

• Real-time Weather Data: Access current conditions from personal weather stations
• Weather Forecasts: Get hourly and daily forecasts with professional meteorological models
• Station Management: Discover and manage multiple weather stations
• Device Information: Detailed metadata about connected weather devices
• Intelligent Caching: Automatic caching with configurable TTL for optimal performance
• Multiple Access Methods: Both tools (interactive queries) and resources (data access)
• Comprehensive Data: Temperature, humidity, pressure, wind, precipitation, solar radiation, UV index, and lightning detection

🚀 Quick Start

Prerequisites

• Python 3.13 or higher
• WeatherFlow API token (get one at tempestwx.com/settings/tokens)

Installation

While each client has its own way of specifying, you'll generally use the following values:

Field	Value
Command	uvx
Arguments	mcp-server-tempest
Environment	WEATHERFLOW_API_TOKEN = <YOUR TOKEN>

Development Version

If you'd like to use the latest and greatest, the server can be pulled straight from GitHub. Just add an additional --from argument:

Field	Value
Command	uvx
Arguments	--from, git+https://github.com/briandconnelly/mcp-server-tempest, mcp-server-tempest
Environment	WEATHERFLOW_API_TOKEN = <YOUR TOKEN>

📋 Configuration

Environment Variables

Variable	Description	Default	Required
WEATHERFLOW_API_TOKEN	Your WeatherFlow API token	-	✅ Yes
WEATHERFLOW_CACHE_TTL	Cache timeout in seconds	300	No
WEATHERFLOW_CACHE_SIZE	Maximum cache entries	100	No

🛠️ Usage

Available Tools

get_stations()

Get a list of all your weather stations and connected devices.

# Get all available stations
stations = await client.call_tool("get_stations")
for station in stations.stations:
    print(f"Station: {station.name} (ID: {station.station_id})")
    print(f"Location: {station.latitude}, {station.longitude}")

get_observation(station_id)

Get current weather conditions for a specific station.

# Get current conditions
obs = await client.call_tool("get_observation", {"station_id": 12345})
current = obs.obs[0]
print(f"Temperature: {current.air_temperature}°")
print(f"Humidity: {current.relative_humidity}%")
print(f"Wind: {current.wind_avg} {obs.station_units.units_wind}")

get_forecast(station_id)

Get weather forecast and current conditions.

# Get forecast
forecast = await client.call_tool("get_forecast", {"station_id": 12345})

# Current conditions
current = forecast.current_conditions
print(f"Current: {current.air_temperature}°")
print(f"Conditions: {current.conditions}")

# Today's forecast
today = forecast.forecast.daily[0]
print(f"High/Low: {today.air_temp_high}°/{today.air_temp_low}°")
print(f"Rain chance: {today.precip_probability}%")

get_station_id(station_id)

Get detailed information about a specific station.

# Get station details
station = await client.call_tool("get_station_id", {"station_id": 12345})
print(f"Station: {station.name}")
print(f"Elevation: {station.station_meta.elevation}m")
print(f"Devices: {len(station.devices)}")

clear_cache()

Clear the data cache (useful for testing).

# Clear cache
await client.call_tool("clear_cache")

Available Resources

The server also provides resources for data access:

• weather://tempest/stations - List all stations
• weather://tempest/stations/{station_id} - Station details
• weather://tempest/observations/{station_id} - Current observations
• weather://tempest/forecast/{station_id} - Weather forecast

🌟 Examples

Basic Weather Check

# Get your stations
stations = await client.call_tool("get_stations")
station_id = stations.stations[0].station_id

# Get current conditions
obs = await client.call_tool("get_observation", {"station_id": station_id})
current = obs.obs[0]

print(f"🌡️  Temperature: {current.air_temperature}°{obs.station_units.units_temp}")
print(f"💧 Humidity: {current.relative_humidity}%")
print(f"💨 Wind: {current.wind_avg} {obs.station_units.units_wind}")
print(f"🌧️  Precipitation: {current.precip_accum_local_day} {obs.station_units.units_precip}")

Weather Forecast

# Get forecast
forecast = await client.call_tool("get_forecast", {"station_id": station_id})

# Today's weather
today = forecast.forecast.daily[0]
print(f"📅 Today: {today.conditions}")
print(f"🌡️  High: {today.air_temp_high}° / Low: {today.air_temp_low}°")
print(f"🌧️  Rain chance: {today.precip_probability}%")

# Next few hours
for hour in forecast.forecast.hourly[:6]:
    time = datetime.fromtimestamp(hour.time)
    print(f"🕐 {time.strftime('%H:%M')}: {hour.air_temperature}° - {hour.conditions}")

Station Information

# Get station details
station = await client.call_tool("get_station_id", {"station_id": station_id})

print(f"🏠 Station: {station.name}")
print(f"📍 Location: {station.latitude}°, {station.longitude}°")
print(f"⛰️  Elevation: {station.station_meta.elevation}m")
print(f"🕐 Timezone: {station.timezone}")

# Check device status
for device in station.devices:
    if device.serial_number:
        status = "🟢 Online" if device.device_meta else "🔴 Offline"
        print(f"📡 {device.device_type}: {status}")

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• WeatherFlow for providing the Tempest weather station and API
• Model Context Protocol for the MCP specification
• FastMCP for the MCP server framework

📞 Support

• Issues: GitHub Issues
• Documentation: WeatherFlow API Docs
• Community: WeatherFlow Community