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walidsi
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.gitignore vendored Normal file
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.env
.venv
uv.lock
.cache.sqlite

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3.13

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LICENSE Normal file
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This is free and unencumbered software released into the public domain.
Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.
In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit
of the public at large and to the detriment of our heirs and
successors. We intend this dedication to be an overt act of
relinquishment in perpetuity of all present and future rights to this
software under copyright law.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
For more information, please refer to <https://unlicense.org>

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README.md Normal file
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# MCP Weather Server
A simple MCP server that provides hourly weather forecasts using the AccuWeather API.
## Setup
1. Install dependencies using `uv`:
```bash
uv venv
uv sync
```
## Running the Server
```json
{
"mcpServers": {
"open_meteo_weather": {
}
}
}
```
## API Usage
### Get 7-dy Weather Forecast
Response:
```json
{
}
```
## The API provides:

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"""MCP Weather - Weather forecast tool for MCP."""
__version__ = "0.1.0"

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import os
import json
from pathlib import Path
from typing import Dict, Optional
from fastmcp import FastMCP
from geopy.geocoders import Nominatim
import openmeteo_requests
import pandas as pd
import requests_cache
from retry_requests import retry
# Initialize FastMCP
mcp = FastMCP("openmeteo-weather-mcp")
# Setup the Open-Meteo API client with cache and retry on error
cache_session = requests_cache.CachedSession(".cache", expire_after=3600)
retry_session = retry(cache_session, retries=5, backoff_factor=0.2)
openmeteo = openmeteo_requests.Client(session=retry_session)
geolocator = Nominatim(user_agent="openmeteo-weather-mcp")
def get_lat_long(location_string: str):
"""
Gets the latitude and longitude of a location string using Nominatim.
Args:
location_string: The location string (e.g., "Paris, France").
Returns:
A tuple containing (latitude, longitude) or None if the location is not found.
"""
try:
location = geolocator.geocode(location_string)
if location:
return (location.latitude, location.longitude)
else:
return None
except Exception as e:
print(f"Error geocoding location: {e}")
return None
@mcp.tool()
async def get_7day_weather(location: str) -> Dict:
"""Get hourly weather forecast for a location."""
# Make sure all required weather variables are listed here
# The order of variables in hourly or daily is important to assign them correctly below
url = "https://api.open-meteo.com/v1/forecast"
lat, long = get_lat_long(location)
params = {
"latitude": lat,
"longitude": long,
"hourly": ["temperature_2m", "relative_humidity_2m", "precipitation"],
}
responses = openmeteo.weather_api(url, params=params)
# Process first location. Add a for-loop for multiple locations or weather models
response = responses[0]
print(f"Coordinates {response.Latitude()}°N {response.Longitude()}°E")
print(f"Elevation {response.Elevation()} m asl")
print(f"Timezone {response.Timezone()}{response.TimezoneAbbreviation()}")
print(f"Timezone difference to GMT+0 {response.UtcOffsetSeconds()} s")
# Process hourly data. The order of variables needs to be the same as requested.
hourly = response.Hourly()
hourly_temperature_2m = hourly.Variables(0).ValuesAsNumpy()
hourly_relative_humidity_2m = hourly.Variables(1).ValuesAsNumpy()
hourly_precipitation = hourly.Variables(2).ValuesAsNumpy()
hourly_data = {
"date": pd.date_range(
start=pd.to_datetime(hourly.Time(), unit="s", utc=True),
end=pd.to_datetime(hourly.TimeEnd(), unit="s", utc=True),
freq=pd.Timedelta(seconds=hourly.Interval()),
inclusive="left",
)
}
hourly_data["temperature_2m"] = hourly_temperature_2m
hourly_data["relative_humidity_2m"] = hourly_relative_humidity_2m
hourly_data["precipitation"] = hourly_precipitation
hourly_dataframe = pd.DataFrame(data=hourly_data)
return hourly_dataframe.to_dict(orient="records")
@mcp.tool()
async def get_current_weather(location: str) -> Dict:
"""Get current weather forecast for a location."""
# Make sure all required weather variables are listed here
# The order of variables in hourly or daily is important to assign them correctly below
url = "https://api.open-meteo.com/v1/forecast"
lat, long = get_lat_long(location)
params = {
"latitude": lat,
"longitude": long,
"current": [
"temperature_2m",
"relative_humidity_2m",
"apparent_temperature",
"precipitation",
"weather_code",
"wind_speed_10m",
"wind_direction_10m",
],
}
responses = openmeteo.weather_api(url, params=params)
# Process first location. Add a for-loop for multiple locations or weather models
response = responses[0]
print(f"Coordinates {response.Latitude()}°N {response.Longitude()}°E")
print(f"Elevation {response.Elevation()} m asl")
print(f"Timezone {response.Timezone()}{response.TimezoneAbbreviation()}")
print(f"Timezone difference to GMT+0 {response.UtcOffsetSeconds()} s")
# Current values. The order of variables needs to be the same as requested.
current = response.Current()
current_temperature_2m = current.Variables(0).Value()
current_relative_humidity_2m = current.Variables(1).Value()
current_apparent_temperature = current.Variables(2).Value()
current_precipitation = current.Variables(3).Value()
current_weather_code = current.Variables(4).Value()
current_wind_speed_10m = current.Variables(5).Value()
current_wind_direction_10m = current.Variables(6).Value()
current_dict = {
"temperature_2m": current_temperature_2m,
"relative_humidity_2m": current_relative_humidity_2m,
"apparent_temperature": current_apparent_temperature,
"precipitation": current_precipitation,
"weather_code": current_weather_code,
"wind_speed_10m": current_wind_speed_10m,
"wind_direction_10m": current_wind_direction_10m,
}
to_json = json.dumps(current_dict)
return to_json
if __name__ == "__main__":
# Initialize and run the server
mcp.run(transport="stdio")

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pyproject.toml Normal file
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[project]
name = "openmeteo-weather-mcp"
version = "0.1.0"
requires-python = ">=3.13"
description = "Weather forecast tool for MCP"
authors = []
dependencies = [
"fastmcp",
"python-dotenv",
"aiohttp",
"uvicorn",
"geopy",
"pandas",
"requests_cache",
"retry_requests",
"openmeteo_requests"
]
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project.scripts]
openmeteo-weather-mcp = "openmeteo_weather.openmeteo_weather:mcp.run"
[tool.hatch.build.targets.wheel]
packages = ["openmeteo_weather.py"]