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Weather MCP Server

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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

Related MCP server: WeatherMCP

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 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:

  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." }
One-click Deploy
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

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