Weather MCP Server

mcp-name: io.github.isdaniel/mcp_weather_server

A Model Context Protocol (MCP) server that provides weather information using the Open-Meteo API. This server supports multiple transport modes: standard stdio, HTTP Server-Sent Events (SSE), and the new Streamable HTTP protocol for web-based integration.

Features

Weather & Air Quality

Get current weather information with comprehensive metrics:
- Temperature, humidity, dew point
- Wind speed, direction, and gusts
- Precipitation (rain/snow) and probability
- Atmospheric pressure and cloud cover
- UV index and visibility
- "Feels like" temperature
Get weather data for a date range with hourly details
Get air quality information including:
- PM2.5 and PM10 particulate matter
- Ozone, nitrogen dioxide, carbon monoxide
- Sulfur dioxide, ammonia, dust
- Aerosol optical depth
- Health advisories and recommendations

Time & Timezone

Get current date/time in any timezone
Convert time between timezones
Get timezone information

Transport Modes

Multiple transport modes:
- stdio - Standard MCP for desktop clients (Claude Desktop, etc.)
- SSE - Server-Sent Events for web applications
- streamable-http - Modern MCP Streamable HTTP protocol with stateful/stateless options
RESTful API endpoints via Starlette integration

Installation

Installing via Smithery

To install Weather MCP Server automatically via Smithery:

npx -y @smithery/cli install @isdaniel/mcp_weather_server

Standard Installation (for MCP clients like Claude Desktop)

This package can be installed using pip:

pip install mcp_weather_server

Manual Configuration for MCP Clients

This server is designed to be installed manually by adding its configuration to the cline_mcp_settings.json file.

Add the following entry to the mcpServers object in your cline_mcp_settings.json file:

{
  "mcpServers": {
    "weather": {
      "command": "python",
      "args": [
        "-m",
        "mcp_weather_server"
      ],
      "disabled": false,
      "autoApprove": []
    }
  }
}

Save the cline_mcp_settings.json file.

HTTP Server Installation (for web applications)

For HTTP SSE or Streamable HTTP support, you'll need additional dependencies:

pip install mcp_weather_server starlette uvicorn

Server Modes

This MCP server supports stdio, SSE, and streamable-http modes in a single unified server:

Mode Comparison

Feature	stdio	SSE	streamable-http
Use Case	Desktop MCP clients	Web applications (legacy)	Web applications (modern)
Protocol	Standard I/O streams	Server-Sent Events	MCP Streamable HTTP
Session Management	N/A	Stateful	Stateful or Stateless
Endpoints	N/A	`/sse`, `/messages/`	`/mcp` (single)
Best For	Claude Desktop, Cline	Browser-based apps	Modern web apps, APIs
State Options	N/A	Stateful only	Stateful or Stateless

1. Standard MCP Mode (Default)

The standard mode communicates via stdio and is compatible with MCP clients like Claude Desktop.

# Default mode (stdio)
python -m mcp_weather_server

# Explicitly specify stdio mode
python -m mcp_weather_server.server --mode stdio

2. HTTP SSE Mode (Web Applications)

The SSE mode runs an HTTP server that provides MCP functionality via Server-Sent Events, making it accessible to web applications.

# Start SSE server on default host/port (0.0.0.0:8080)
python -m mcp_weather_server --mode sse

# Specify custom host and port
python -m mcp_weather_server --mode sse --host localhost --port 3000

# Enable debug mode
python -m mcp_weather_server --mode sse --debug

SSE Endpoints:

GET /sse - SSE endpoint for MCP communication
POST /messages/ - Message endpoint for sending MCP requests

3. Streamable HTTP Mode (Modern MCP Protocol)

The streamable-http mode implements the new MCP Streamable HTTP protocol with a single /mcp endpoint. This mode supports both stateful (default) and stateless operations.

# Start streamable HTTP server on default host/port (0.0.0.0:8080)
python -m mcp_weather_server --mode streamable-http

# Specify custom host and port
python -m mcp_weather_server --mode streamable-http --host localhost --port 3000

# Enable stateless mode (creates fresh transport per request, no session tracking)
python -m mcp_weather_server --mode streamable-http --stateless

# Enable debug mode
python -m mcp_weather_server --mode streamable-http --debug

Streamable HTTP Features:

Stateful mode (default): Maintains session state across requests using session IDs
Stateless mode: Creates fresh transport per request with no session tracking
Single endpoint: All MCP communication happens through /mcp
Modern protocol: Implements the latest MCP Streamable HTTP specification

Streamable HTTP Endpoint:

POST /mcp - Single endpoint for all MCP communication (initialize, tools/list, tools/call, etc.)

Command Line Options:

--mode {stdio,sse,streamable-http}  Server mode: stdio (default), sse, or streamable-http
--host HOST                          Host to bind to (HTTP modes only, default: 0.0.0.0)
--port PORT                          Port to listen on (HTTP modes only, default: 8080)
--stateless                          Run in stateless mode (streamable-http only)
--debug                              Enable debug mode

Example SSE Usage:

// Connect to SSE endpoint
const eventSource = new EventSource('http://localhost:8080/sse');

// Send MCP tool request
fetch('http://localhost:8080/messages/', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    type: 'tool_call',
    tool: 'get_weather',
    arguments: { city: 'Tokyo' }
  })
});

Example Streamable HTTP Usage:

// Initialize session and call tool using Streamable HTTP protocol
async function callWeatherTool() {
  const response = await fetch('http://localhost:8080/mcp', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      jsonrpc: '2.0',
      method: 'tools/call',
      params: {
        name: 'get_current_weather',
        arguments: { city: 'Tokyo' }
      },
      id: 1
    })
  });

  const result = await response.json();
  console.log(result);
}

Configuration

This server does not require an API key. It uses the Open-Meteo API, which is free and open-source.

Usage

This server provides several tools for weather and time-related operations:

Available Tools

Weather Tools

get_current_weather - Get current weather for a city with comprehensive metrics
get_weather_by_datetime_range - Get weather data for a date range with hourly details
get_weather_details - Get detailed weather information as structured JSON data

Air Quality Tools

get_air_quality - Get air quality information with pollutant levels and health advice
get_air_quality_details - Get detailed air quality data as structured JSON

Time & Timezone Tools

get_current_datetime - Get current time in any timezone
get_timezone_info - Get timezone information
convert_time - Convert time between timezones

Tool Details

`get_current_weather`

Retrieves comprehensive current weather information for a given city with enhanced metrics.

Parameters:

city (string, required): The name of the city (English names only)

Returns: Detailed weather data including:

Temperature and "feels like" temperature
Humidity, dew point
Wind speed, direction (as compass direction), and gusts
Precipitation details (rain/snow) and probability
Atmospheric pressure and cloud cover
UV index with warning levels
Visibility

Example Response:

The weather in Tokyo is Mainly clear with a temperature of 22.5°C (feels like 21.0°C),
relative humidity at 65%, and dew point at 15.5°C. Wind is blowing from the NE at 12.5 km/h
with gusts up to 18.5 km/h. Atmospheric pressure is 1013.2 hPa with 25% cloud cover.
UV index is 5.5 (Moderate). Visibility is 10.0 km.

`get_weather_by_datetime_range`

Retrieves hourly weather information with comprehensive metrics for a specified city between start and end dates.

Parameters:

city (string, required): The name of the city (English names only)
start_date (string, required): Start date in format YYYY-MM-DD (ISO 8601)
end_date (string, required): End date in format YYYY-MM-DD (ISO 8601)

Returns: Comprehensive weather analysis including:

Hourly weather data with all enhanced metrics
Temperature trends (highs, lows, averages)
Precipitation patterns and probabilities
Wind conditions assessment
UV index trends
Weather warnings and recommendations

Example Response:

[Analysis of weather trends over 2024-01-01 to 2024-01-07]
- Temperature ranges from 5°C to 15°C
- Precipitation expected on Jan 3rd and 5th (60% probability)
- Wind speeds averaging 15 km/h from SW direction
- UV index moderate (3-5) throughout the period
- Recommendation: Umbrella needed for midweek

`get_weather_details`

Get detailed weather information for a specified city as structured JSON data for programmatic use.

Parameters:

city (string, required): The name of the city (English names only)

Returns: Raw JSON data with all weather metrics suitable for processing and analysis

`get_air_quality`

Get current air quality information for a specified city with pollutant levels and health advisories.

Parameters:

city (string, required): The name of the city (English names only)
variables (array, optional): Specific pollutants to retrieve. Options:
- pm10 - Particulate matter ≤10μm
- pm2_5 - Particulate matter ≤2.5μm
- carbon_monoxide - CO levels
- nitrogen_dioxide - NO2 levels
- ozone - O3 levels
- sulphur_dioxide - SO2 levels
- ammonia - NH3 levels
- dust - Dust particle levels
- aerosol_optical_depth - Atmospheric turbidity

Returns: Comprehensive air quality report including:

Current pollutant levels with units
Air quality classification (Good/Moderate/Unhealthy/Hazardous)
Health recommendations for general population
Specific warnings for sensitive groups
Comparison with WHO and EPA standards

Example Response:

Air quality in Beijing (lat: 39.90, lon: 116.41):
PM2.5: 45.3 μg/m³ (Unhealthy for Sensitive Groups)
PM10: 89.2 μg/m³ (Moderate)
Ozone (O3): 52.1 μg/m³
Nitrogen Dioxide (NO2): 38.5 μg/m³
Carbon Monoxide (CO): 420.0 μg/m³

Health Advice: Sensitive groups (children, elderly, people with respiratory conditions)
should limit outdoor activities.

`get_air_quality_details`

Get detailed air quality information as structured JSON data for programmatic analysis.

Parameters:

city (string, required): The name of the city (English names only)
variables (array, optional): Specific pollutants to retrieve (same options as get_air_quality)

Returns: Raw JSON data with complete air quality metrics and hourly data

`get_current_datetime`

Retrieves the current time in a specified timezone.

Parameters:

timezone_name (string, required): IANA timezone name (e.g., 'America/New_York', 'Europe/London'). Use UTC if no timezone provided.

Returns: Current date and time in the specified timezone

Example:

{
  "timezone": "America/New_York",
  "current_time": "2024-01-15T14:30:00-05:00",
  "utc_time": "2024-01-15T19:30:00Z"
}

`get_timezone_info`

Get information about a specific timezone.

Parameters:

timezone_name (string, required): IANA timezone name

Returns: Timezone details including offset and DST information

`convert_time`

Convert time from one timezone to another.

Parameters:

time_str (string, required): Time to convert (ISO format)
from_timezone (string, required): Source timezone
to_timezone (string, required): Target timezone

Returns: Converted time in target timezone

MCP Client Usage Examples

Using with Claude Desktop or MCP Clients

<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_current_weather</tool_name>
<arguments>
{
  "city": "Tokyo"
}
</arguments>
</use_mcp_tool>

<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_weather_by_datetime_range</tool_name>
<arguments>
{
  "city": "Paris",
  "start_date": "2024-01-01",
  "end_date": "2024-01-07"
}
</arguments>
</use_mcp_tool>

<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_current_datetime</tool_name>
<arguments>
{
  "timezone_name": "Europe/Paris"
}
</arguments>
</use_mcp_tool>

<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_air_quality</tool_name>
<arguments>
{
  "city": "Beijing"
}
</arguments>
</use_mcp_tool>

<use_mcp_tool>
<server_name>weather</server_name>
<tool_name>get_air_quality</tool_name>
<arguments>
{
  "city": "Los Angeles",
  "variables": ["pm2_5", "pm10", "ozone"]
}
</arguments>
</use_mcp_tool>

Web Integration (SSE Mode)

When running in SSE mode, you can integrate the weather server with web applications:

HTML/JavaScript Example

<!DOCTYPE html>
<html>
<head>
    <title>Weather MCP Client</title>
</head>
<body>
    <div id="weather-data"></div>
    <script>
        // Connect to SSE endpoint
        const eventSource = new EventSource('http://localhost:8080/sse');

        eventSource.onmessage = function(event) {
            const data = JSON.parse(event.data);
            document.getElementById('weather-data').innerHTML = JSON.stringify(data, null, 2);
        };

        // Function to get weather
        async function getWeather(city) {
            const response = await fetch('http://localhost:8080/messages/', {
                method: 'POST',
                headers: { 'Content-Type': 'application/json' },
                body: JSON.stringify({
                    jsonrpc: '2.0',
                    method: 'tools/call',
                    params: {
                        name: 'get_current_weather',
                        arguments: { city: city }
                    },
                    id: 1
                })
            });
        }

        // Example: Get weather for Tokyo
        getWeather('Tokyo');

        // Example: Get air quality
        async function getAirQuality(city) {
            const response = await fetch('http://localhost:8080/messages/', {
                method: 'POST',
                headers: { 'Content-Type': 'application/json' },
                body: JSON.stringify({
                    jsonrpc: '2.0',
                    method: 'tools/call',
                    params: {
                        name: 'get_air_quality',
                        arguments: { city: city }
                    },
                    id: 2
                })
            });
        }

        getAirQuality('Beijing');
    </script>
</body>
</html>

Docker Deployment

The project is available as a Docker image on Docker Hub and includes configurations for easy deployment.

Quick Start with Docker Hub

Pull and run the latest image directly from Docker Hub:

# Pull the latest image
docker pull dog830228/mcp_weather_server:latest

# Run in stdio mode (default)
docker run dog830228/mcp_weather_server:latest

# Run in SSE mode on port 8080
docker run -p 8080:8080 dog830228/mcp_weather_server:latest --mode sse

# Run in streamable-http mode on port 8080
docker run -p 8080:8080 dog830228/mcp_weather_server:latest --mode streamable-http

# Pull a specific version
docker pull dog830228/mcp_weather_server:0.5.0
docker run -p 8080:8080 dog830228/mcp_weather_server:0.5.0 --mode sse

Available Docker Images

Latest: dog830228/mcp_weather_server:latest
Versioned: dog830228/mcp_weather_server:<version> (e.g., 0.5.0)

Images are automatically built and published when new versions are released.

Building from Source

If you want to build the Docker image yourself:

Standard Build

# Build
docker build -t mcp-weather-server:sse .

# Run (port will be read from PORT env var, defaults to 8081)
docker run -p 8081:8081 mcp-weather-server:sse

# Run with custom port
docker run -p 8080:8080 mcp-weather-server:local --mode sse

Streamable HTTP Build

# Build using streamable-http Dockerfile
docker build -f Dockerfile.streamable-http -t mcp-weather-server:streamable-http .

# Run in stateful mode
docker run -p 8080:8080 mcp-weather-server:streamable-http

# Run in stateless mode
docker run -p 8080:8080 -e STATELESS=true mcp-weather-server:streamable-http

Development

Project Structure

mcp_weather_server/
├── src/
│   └── mcp_weather_server/
│       ├── __init__.py
│       ├── __main__.py          # Main MCP server entry point
│       ├── server.py            # Unified server (stdio, SSE, streamable-http)
│       ├── utils.py             # Utility functions
│       └── tools/               # Tool implementations
│           ├── __init__.py
│           ├── toolhandler.py   # Base tool handler
│           ├── tools_weather.py # Weather-related tools
│           ├── tools_time.py    # Time-related tools
│           ├── tools_air_quality.py # Air quality tools
│           ├── weather_service.py   # Weather API service
│           └── air_quality_service.py # Air quality API service
├── tests/
├── Dockerfile                   # Docker configuration for SSE mode
├── Dockerfile.streamable-http   # Docker configuration for streamable-http mode
├── pyproject.toml
├── requirements.txt
└── README.md

Running for Development

Standard MCP Mode (stdio)

# From project root
python -m mcp_weather_server

# Or with PYTHONPATH
export PYTHONPATH="/path/to/mcp_weather_server/src"
python -m mcp_weather_server

SSE Server Mode

# From project root
python -m mcp_weather_server --mode sse --host 0.0.0.0 --port 8080

# With custom host/port
python -m mcp_weather_server --mode sse --host localhost --port 3000

Streamable HTTP Mode

# Stateful mode (default)
python -m mcp_weather_server --mode streamable-http --host 0.0.0.0 --port 8080

# With debug logging
python -m mcp_weather_server --mode streamable-http --debug

Adding New Tools

To add new weather or time-related tools:

Create a new tool handler in the appropriate file under tools/
Inherit from the ToolHandler base class
Implement the required methods (get_name, get_description, call)
Register the tool in server.py

Dependencies

Core Dependencies

mcp>=1.0.0 - Model Context Protocol implementation
httpx>=0.28.1 - HTTP client for API requests
python-dateutil>=2.8.2 - Date/time parsing utilities

SSE Server Dependencies

starlette - ASGI web framework
uvicorn - ASGI server

Development Dependencies

pytest - Testing framework

API Data Sources

This server uses free and open-source APIs:

Weather Data: Open-Meteo Weather API

Free and open-source
No API key required
Provides accurate weather forecasts
Supports global locations
Historical and current weather data
Comprehensive metrics (wind, precipitation, UV, visibility)

Air Quality Data:

Free and open-source
No API key required
Real-time air quality data
Multiple pollutant measurements (PM2.5, PM10, O3, NO2, CO, SO2)
Global coverage
Health-based air quality indices

Troubleshooting

Common Issues

1. City not found

Ensure city names are in English
Try using the full city name or include country (e.g., "Paris, France")
Check spelling of city names

2. HTTP Server not accessible (SSE or Streamable HTTP)

Verify the server is running with the correct mode:
- SSE: python -m mcp_weather_server --mode sse
- Streamable HTTP: python -m mcp_weather_server --mode streamable-http
Check firewall settings for the specified port
Ensure all dependencies are installed: pip install starlette uvicorn
Verify the correct endpoint:
- SSE: http://localhost:8080/sse and http://localhost:8080/messages/
- Streamable HTTP: http://localhost:8080/mcp

3. MCP Client connection issues

Verify Python path in MCP client configuration
Check that mcp_weather_server package is installed
Ensure Python environment has required dependencies

4. Date format errors

Use ISO 8601 format for dates: YYYY-MM-DD
Ensure start_date is before end_date
Check that dates are not too far in the future

Error Responses

The server returns structured error messages:

{
  "error": "Could not retrieve coordinates for InvalidCity."
}

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