Weather MCP 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.

1. 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": []
    }
  }
}

1. 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

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

Air Quality Tools

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

Time & Timezone Tools

1. get_current_datetime - Get current time in any timezone
2. get_timezone_info - Get timezone information
3. 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 includes Docker configurations for easy deployment:

SSE Mode Docker

# 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 -e PORT=8080 mcp-weather-server:sse

Streamable HTTP Mode Docker

# 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:

1. Create a new tool handler in the appropriate file under tools/
2. Inherit from the ToolHandler base class
3. Implement the required methods (get_name, get_description, call)
4. 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."
}