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PyWeatherEnriched MCP 2.0 Quick Start

AI-native weather enrichment. Ask Claude to correlate business metrics with weather, forecast impact, find anomalies.

Installation

pip install PyWeatherEnriched>=1.0

Basic Usage

from pyweatherenriched import WeatherEnricher

# Create enricher
enricher = WeatherEnricher()

# Enable MCP (starts on port 8769)
endpoint = enricher.start_mcp_connector()

# Claude can now:
# - "Which locations were affected by storms last week?"
# - "Correlate our sales with rainfall events"
# - "Show enrichment coverage by region"
# - "Forecast weather impact on revenue next week"

10 MCP Tools

  1. get_enrichment_status — Coverage & data quality by location
  2. query_enriched_data — Time-series weather metrics
  3. get_weather_events — Storm, heat, cold, flood detection
  4. get_location_coverage — Regional coverage gaps
  5. detect_weather_anomalies — Find unusual patterns
  6. correlate_business_metric — Link sales/traffic to weather
  7. forecast_weather_impact — Predict impact on business
  8. export_enriched_data — Multi-format export
  9. validate_enrichment_quality — Quality assessment
  10. get_hyperlocal_weather — Neighborhood-level precision

For full documentation, see README.md