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MCP Server for Retrieving Tempest Weather Data

Project description

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
  • Tools for interactive queries and structured weather data
  • Comprehensive Data: Temperature, humidity, pressure, wind, precipitation, solar radiation, UV index, and lightning detection

🚀 Quick Start

Prerequisites

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 In-memory cache TTL in seconds 300 No
WEATHERFLOW_CACHE_SIZE Maximum in-memory cache entries 100 No
WEATHERFLOW_DISK_CACHE_TTL Disk cache TTL in seconds 86400 No

Caching & data freshness

The server caches responses in two layers:

  • In-memory (WEATHERFLOW_CACHE_TTL / WEATHERFLOW_CACHE_SIZE): all four tools.
  • On disk (WEATHERFLOW_DISK_CACHE_TTL, default 24h): tempest_get_stations and tempest_get_station_details only. Stored under platformdirs.user_cache_dir("mcp-server-tempest") in a per-token (hash-keyed) subdirectory.

To clear: restart the server (in-memory) or delete the cache directory (disk).

Transport

stdio (the default for uvx mcp-server-tempest and the README config).

🛠️ Usage

Available Tools

tempest_get_stations()

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

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

tempest_get_observation(station_id)

Get current weather conditions for a specific station.

# Get current conditions
obs = await client.call_tool("tempest_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']}")

tempest_get_forecast(station_id)

Get weather forecast and current conditions.

# Get forecast
forecast = await client.call_tool("tempest_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']}%")

tempest_get_station_details(station_id)

Get detailed information about a specific station.

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

🌟 Examples

Basic Weather Check

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

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

print(f"🌡️  Temperature: {current['air_temperature']}°{units['units_temp']}")
print(f"💧 Humidity: {current['relative_humidity']}%")
print(f"💨 Wind: {current['wind_avg']} {units['units_wind']}")
print(f"🌧️  Precipitation: {current['precip_accum_local_day']} {units['units_precip']}")

Weather Forecast

from datetime import datetime

# Get forecast
forecast = await client.call_tool("tempest_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("tempest_get_station_details", {"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.get("serial_number"):
        status = "🟢 Online" if device.get("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

📞 Support

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