MCP Weather Server
Provides hourly weather forecasts using the AccuWeather API, including current conditions and 12-hour forecast with temperature, precipitation, and weather description.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Weather Serverwhat's the weather in Tokyo?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Weather Server
A simple MCP server that provides hourly weather forecasts using the AccuWeather API.
Setup
Install dependencies using
uv:
uv venv
uv syncCreate a
.envfile with your AccuWeather API key:
ACCUWEATHER_API_KEY=your_api_key_hereYou can get an API key by registering at AccuWeather API.
Related MCP server: Weather MCP Server
Running the Server
STDIO Mode (Default)
For local MCP client connections via stdio:
{
"mcpServers": {
"weather": {
"command": "uvx",
"args": ["--from", "git+https://github.com/adhikasp/mcp-weather.git", "mcp-weather"],
"env": {
"ACCUWEATHER_API_KEY": "your_api_key_here"
}
}
}
}HTTP Streaming Mode
To run the server as a streamable HTTP server:
Option 1: Using the command line
python -m mcp_weather.weather --httpOption 2: Using the entry point
mcp-weather-httpOption 3: Using environment variables
export MCP_HOST=0.0.0.0
export MCP_PORT=8000
python -m mcp_weather.weather --httpThe server will start on http://0.0.0.0:8000 (or your specified host/port) and expose the MCP endpoint at /mcp. The streamable-http transport supports:
JSON responses for standard requests
Server-Sent Events (SSE) for streaming long-running operations
Remote access via HTTP endpoints
Horizontal scaling with load balancing
Connecting to HTTP Server:
For MCP clients that support HTTP transport, configure the connection URL:
http://localhost:8000/mcpAgent UI Configuration:
When configuring your MCP server in the Agent UI (e.g., Cursor, Claude Desktop, etc.):
URL: Provide the full endpoint URL (e.g.,
http://localhost:8000/mcporhttps://your-ngrok-url.ngrok.io/mcp)Authentication: Not required by default - No API keys, tokens, or scopes need to be configured in the Agent UI
Headers: No custom headers needed for basic operation
The MCP protocol handles communication automatically. Your AccuWeather API key is stored server-side and never needs to be shared with the client.
Note: If you implement custom authentication (API keys, tokens) at the HTTP layer for production use, you would configure those in your server code, not in the Agent UI. The Agent UI would then need to include those credentials in HTTP requests, but this is not needed for basic operation.
Production Deployment:
For production, you can use environment variables or configure a reverse proxy:
# Set custom host and port
export MCP_HOST=0.0.0.0
export MCP_PORT=8080
mcp-weather-httpExposing via Public URL (Tunneling)
To make your local server accessible via a public URL, use a tunneling service:
Option 1: ngrok (Recommended)
Install ngrok on Windows:
Option A: Using winget (Windows 10/11 - Recommended)
winget install ngrok.ngrokOption B: Using Chocolatey (if you have Chocolatey installed)
choco install ngrokOption C: Manual Download
Go to ngrok.com/download
Download the Windows ZIP file
Extract
ngrok.exeto a folder (e.g.,C:\ngrok)Add that folder to your PATH, or run ngrok from that folder
Or simply run:
.\ngrok.exe http 8000from the extracted folder
Option D: Using Scoop (if you have Scoop installed)
scoop install ngrokAfter installation, verify it works:
ngrok versionStart your MCP server:
python -m mcp_weather.weather --httpCreate a tunnel (in a separate terminal):
ngrok http 8000Use the public URL: ngrok will provide a public URL like
https://abc123.ngrok-free.dev.Important: The MCP endpoint is at
/mcp, not the root URL. Use:https://abc123.ngrok-free.dev/mcpNote about ngrok warning page: Free ngrok accounts show a warning page when visiting the root URL. This is normal and expected. The
/mcpendpoint will work correctly for MCP clients. To remove the warning page, you can:Upgrade to a paid ngrok account
Set the
ngrok-skip-browser-warningheader in your MCP client (if supported)Use a custom domain with a paid account
For a custom domain (requires paid ngrok account):
ngrok http 8000 --domain=your-custom-domain.ngrok.io
Option 2: Cloudflare Tunnel (cloudflared)
Install cloudflared: Download from developers.cloudflare.com
Start your MCP server:
python -m mcp_weather.weather --httpCreate a tunnel (in a separate terminal):
cloudflared tunnel --url http://localhost:8000Use the public URL: Cloudflare will provide a public URL like
https://random-subdomain.trycloudflare.com. Your MCP endpoint will be:https://random-subdomain.trycloudflare.com/mcp
Option 3: localtunnel
Install localtunnel:
npm install -g localtunnelStart your MCP server:
python -m mcp_weather.weather --httpCreate a tunnel (in a separate terminal):
lt --port 8000Use the public URL: localtunnel will provide a public URL like
https://random-name.loca.lt. Your MCP endpoint will be:https://random-name.loca.lt/mcp
Security Note: When exposing your server publicly, consider:
Adding authentication/API keys if your MCP server handles sensitive data
Using HTTPS (all tunneling services above provide HTTPS)
Limiting access to specific IPs if possible
Monitoring usage and rate limiting
API Usage
Get Hourly Weather Forecast
Response:
{
"location": "Jakarta",
"location_key": "208971",
"country": "Indonesia",
"current_conditions": {
"temperature": {
"value": 32.2,
"unit": "C"
},
"weather_text": "Partly sunny",
"relative_humidity": 75,
"precipitation": false,
"observation_time": "2024-01-01T12:00:00+07:00"
},
"hourly_forecast": [
{
"relative_time": "+1 hour",
"temperature": {
"value": 32.2,
"unit": "C"
},
"weather_text": "Partly sunny",
"precipitation_probability": 40,
"precipitation_type": "Rain",
"precipitation_intensity": "Light"
}
]
}The API provides:
Current weather conditions including temperature, weather description, humidity, and precipitation status
12-hour forecast with hourly data including:
Relative time from current time
Temperature in Celsius
Weather description
Precipitation probability, type, and intensity
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