Lift Capacity & Timing Engine

Lift Capacity & Timing Engine MCP Connector for Claude

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Calculate lift line wait times, optimal cycle durations, and daily operational capacity.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides analytical tools for ski resort operations. It uses queue theory to model lift line dynamics. Use get_estimated_wait_time to predict queue duration based on resort density, calculate_optimal_cycle_time to balance throughput, simulate_daily_operations to forecast daily capacity including lunch rush impacts, and compare_lift_options to select the most efficient hardware configuration for specific crowds.

ski-resortqueue-theorycapacity-planninglogisticsoperations-management

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

calculate_optimal_cycle_time

Calculate the most efficient duration for a single lift cycle

compare_lift_options

Compare different lift configurations for a specific crowd

get_estimated_wait_time

Calculate the estimated wait time in minutes for the current lift line

simulate_daily_operations

Simulate total daily lift operations

See how to talk to your AI agent using Lift Capacity & Timing Engine.

How long is the wait for a lift with 500 capacity, 50 people in line, and a resort density of 1.2?

The estimated wait time is 6 minutes and the queue is stable.

What is the total capacity for a 480-minute operation with a 5-minute cycle time during a lunch rush?

The lift will complete 96 runs with a total daily capacity of 4,800 people.

Calculate the optimal cycle time for a lift with 1200 capacity and 4 people per chair.

The optimal cycle time is 12 minutes, suggesting 300 chairs per hour.

The `get_estimated_wait_time` tool calculates wait times by analyzing the ratio of current queue length to the lift's hourly capacity, adjusted by the resort density factor.

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