genpark-demand-forecasting-skill
GenPark AI Skill - Forecast product demand using historical sales, seasonality decomposition, and trend detection with reorder recommendations
Install / Use
claude mcp add alphaparkinc -- npx -y github:alphaparkinc/genpark-demand-forecasting-skillIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AutomationSupported Platforms
Skill content
View source on GitHubgenpark-demand-forecasting-skill
GenPark AI Agent Skill -- Forecast product demand using historical sales, seasonality decomposition, and trend detection.
Features
- Exponential smoothing baseline forecast
- Linear trend detection (growing / stable / declining)
- Multiplicative seasonality index decomposition
- 80%/120% confidence interval bounds
- Safety stock calculation with lead time adjustment
- Reorder point and suggested order quantity
Quick Start
from client import DemandForecastingClient
client = DemandForecastingClient()
result = client.forecast(
sales_history=[{"period": "Jan", "units_sold": 120}, {"period": "Feb", "units_sold": 135}],
forecast_periods=6,
lead_time_periods=2,
)
print(result["trend"], result["reorder_recommendation"])
Installation
python example_usage.py # No external dependencies
Built by GenPark | alphaparkinc
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