White Noise Sleep Planner

White Noise Sleep Planner MCP Connector for Claude

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Optimizes white noise volume, duration, and sound type for better sleep.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server helps you plan your sleep environment using sound masking principles. It calculates the ideal volume and sound type to mask disturbances, creates duration schedules with fade-out plans, and provides weaning strategies to prevent sudden silence. You can use get_masking_parameters to find the best sound for your environment, get_duration_schedule for timing, get_weaning_strategy for volume reduction, and get_device_optimization to adjust settings for your specific hardware.

sleepwhite-noisesound-maskingwellnessaudio

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

get_device_optimization

Adjusts recommendations based on the technical limitations of the playback hardware

get_duration_schedule

Calculates how long the noise should play and how it should fade

get_masking_parameters

Determines the ideal volume and sound type to mask the current environment

get_weaning_strategy

Provides a step-by-step plan for reducing volume to prevent sudden silence

See how to talk to your AI agent using White Noise Sleep Planner.

I live in a noisy city and have high sensitivity to sound. What white noise settings should I use on my smartphone?

For a noisy city environment and high sensitivity using a smartphone, you should use Brown noise at a volume of 55dB. Since smartphones have limited low-frequency response, it is recommended to increase the volume slightly to compensate.

Plan a 7-hour sleep schedule with a fade-out.

For a 420-minute sleep duration, the noise should play for the full duration, with the fade-out starting at minute 315 and lasting for 105 minutes.

How can I gradually reduce the volume of my white noise?

To reduce volume from 60dB in 3 steps, you should follow this plan: Step 1: 45dB, Step 2: 30dB, Step 3: 15dB.

You can use the `get_masking_parameters` tool. It analyzes your noise environment and sensitivity to recommend white, pink, or brown noise.

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