Peaking Index Calculator

Peaking Index Calculator MCP Connector for Claude

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Model athletic readiness using the Banister Fitness-Fatigue model.

5 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server connects AI agents to the Banister Fitness-Fatigue model, allowing for precise athletic readiness modeling. By analyzing training load and decay rates, agents can use calculate_peaking_index to project performance for specific competition dates. The server also provides tools like assess_readiness to interpret physiological states and predict_peak_day to identify the optimal window for peak performance. It is designed to help coaches and athletes quantify the balance between long-term fitness and short-term fatigue.

athletic-performancefitness-fatiguetraining-loadcoachingreadiness

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

predict_peak_day

Identifies the optimal date for competition to maximize the peaking index

assess_readiness

Provides a qualitative status of the athlete's readiness for competition

calculate_peaking_index

Calculates the net readiness value for a specific competition date

get_fatigue_level

Quantifies the immediate physiological strain accumulated from recent training

get_fitness_level

Determines the current physiological capacity of the athlete based on historical training

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

Based on my training history, when is my best day to compete?

Your optimal competition day is in 12 days, where your predicted peaking index will reach its maximum value.

Calculate my peaking index for a race in 7 days.

Your projected peaking index for the race in 7 days is 42.5, with a fitness level of 85.0 and a fatigue level of 42.5.

Am I ready for my marathon next week?

Your current status is 'Peaked', meaning you are in an optimal state for competition with high fitness and manageable fatigue.

The index is calculated by projecting fitness and fatigue levels forward to a target date. It represents the net difference between the two, where a higher value indicates better readiness.

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