MCP For Claude Marketplace
Seasonality Index Calculator

Seasonality Index Calculator MCP Connector for Claude

A+

Calculate seasonal indices and optimize inventory planning using historical sales data.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides advanced analytical tools to quantify seasonal patterns in sales data. By using calculate_seasonal_indices, you can determine how much each month deviates from the average demand. The analyze_extremes tool identifies peak and trough months, while generate_recommendations suggests specific inventory stocking postures like 'Aggressive' or 'Lean' based on your seasonal indices. It is designed to help businesses transform historical monthly sales records into actionable inventory strategies.

seasonalitysales-forecastinginventory-optimizationdemand-planningdata-analysis

3 tools expose this connector's capabilities to your AI agent.

analyze_extremes

Identifies peak and trough months in the seasonal cycle

calculate_seasonal_indices

Calculates monthly seasonal indices and deseasonalized demand

generate_recommendations

Generates inventory stocking recommendations

See how to talk to your AI agent using Seasonality Index Calculator.

Calculate seasonal indices for this sales data: [{'month': 1, 'sales': 100}, {'month': 2, 'sales': 120}, ...]

The calculation is complete. The seasonal indices show a peak in month 1 and a trough in month 6.

Identify the peak and trough months from these indices: [{'month': 1, 'index': 1.2}, {'month': 2, 'index': 0.8}]

The peak month is month 1 with an index of 1.2, and the trough month is month 2 with an index of 0.8.

Generate inventory recommendations for a base target of 500 units using these indices: [{'month': 1, 'index': 1.5}]

For month 1, an 'Aggressive' stocking posture is recommended with a suggested stock level of 750 units.

A seasonal index quantifies how much a specific period deviates from the long-term average. A value of 1.0 is neutral, above 1.0 indicates a peak, and below 1.0 indicates a trough.

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