Day10 Weather Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Day10 Weather Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Day 10 of the 30-Day RAG Learning Journey focuses on building a Weather MCP Server that integrates with real-time weather APIs. This project combines RAG (Retrieval-Augmented Generation) principles with Location-Based Context Synthesis (LBCS) systems.
day10-weather-mcp/
├── weather_mcp_server.py # Main MCP server with weather tools
├── test_weather.py # Test client for API validation
├── requirements.txt # Python dependencies
├── .env # Environment variables (API keys)
├── .env.example # Template for environment setup
├── README.md # This file
└── venv/ # Virtual environmentReturns comprehensive current weather data:
# Example usage
location = "London"
units = "metric" # or "imperial", "standard"Returns 5-day weather forecast with daily highs/lows:
# Example usage
location = "Paris"
days = 5Returns severe weather warnings and alerts (if any):
# Example usage
location = "New York"Returns side-by-side weather comparison:
# Example usage
location1 = "London"
location2 = "New York"Returns weather for specific latitude/longitude:
# Example usage
lat = 51.5074
lon = -0.1278# Navigate to directory
cd week2-mcp/day10-weather-mcp
# Create and activate virtual environment
python -m venv venv
# Windows
venv\Scripts\activate
# macOS/Linux
source venv/bin/activate
# Install packages
pip install -r requirements.txt# Copy template
cp .env.example .env
# Edit .env and add your API key
# WEATHER_API_KEY=your_actual_api_key_herepython weather_mcp_server.pypython test_weather.pyCurrent Weather in London, GB:
Description: Partly Cloudy
Temperature: 8.5°C
Feels Like: 6.2°C
Humidity: 72%
Wind Speed: 4.5 m/s
Pressure: 1013 hPa
Cloudiness: 40%5-Day Weather Forecast for London:
Date: 2025-12-28
High: 10.2°C | Low: 5.3°C
Conditions: Rainy
--------------------------------------------------
Date: 2025-12-29
High: 9.1°C | Low: 4.8°C
Conditions: Cloudy
--------------------------------------------------Weather Comparison: London vs Paris
============================================================
London | Paris
------------------------------------------------------------
Temperature: 8.5°C | 9.2°C
Feels Like: 6.2°C | 7.1°C
Humidity: 72% | 65%
Conditions: Cloudy| Clear
Wind Speed: 4.5 | 3.2 m/sTo use this MCP server with Claude Desktop:
%APPDATA%\Claude\claude_desktop_config.json~/Library/Application Support/Claude/claude_desktop_config.json{
"mcpServers": {
"weather": {
"command": "python",
"args": ["C:\\path\\to\\weather_mcp_server.py"]
}
}
}This project demonstrates:
"What's the weather like in Tokyo right now?"
Claude uses get_current_weather tool to retrieve current conditions.
"Compare the weather between London, Paris, and New York"
Claude uses compare_locations tool for side-by-side analysis.
"What will the weather be like in Sydney over the next 5 days?"
Claude uses get_forecast tool to get daily predictions.
"Get the weather at coordinates 51.5074, -0.1278"
Claude uses get_weather_by_coords for precise location weather.
"Are there any weather alerts for Los Angeles?"
Claude uses get_weather_alerts to check for severe weather.
.envpip install -r requirements.txtMain MCP server implementation with:
list_tools)call_tool)Test client for validating:
Python package dependencies:
Environment configuration:
To extend this project:
list_tools()weather_mcp_server.pycall_tool() functiontest_weather.pyRithwik Nyalam Date: December 28, 2025 Part of: 30-Day RAG Learning Journey - Week 2
Last Updated: December 28, 2025 Status: Production Ready Version: 1.0.0
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.