MCP For Claude Marketplace
Sleep Efficiency Tracker

Sleep Efficiency Tracker MCP Connector for Claude

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Calculate sleep quality metrics and efficiency from sleep diary data.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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The Sleep Efficiency Tracker provides a detailed analysis of sleep quality by processing sleep diary data. It calculates key metrics such as sleep efficiency percentage, total sleep time, and sleep onset latency. By using the calculate_sleep_metrics tool, users can receive a quality assessment that compares their rest against age-specific benchmarks. You can also use get_efficiency_benchmark to find healthy targets for different life stages or get_quality_description to understand what your efficiency score means for your health.

sleephealth-metricswellnesssleep-qualitybiometrics

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

calculate_sleep_metrics

Provides a comprehensive breakdown of sleep quality metrics for a single night

get_efficiency_benchmark

Retrieves the target sleep efficiency percentage for a specific age group

get_quality_description

Provides a natural language explanation of what a specific efficiency percentage means for a user's health

validate_sleep_diary_entry

Checks if a set of diary inputs is logically consistent before performing calculations

See how to talk to your AI agent using Sleep Efficiency Tracker.

I was in bed for 480 minutes, it took me 30 minutes to fall asleep, and I woke up for 20 minutes during the night. I am 30 years old. How was my sleep?

Your sleep efficiency was 91.67%. Your total sleep time was 430 minutes. This is considered Excellent sleep quality for your age.

What is the target sleep efficiency for a 70-year-old?

The target efficiency for the Senior age group is 85%.

I spent 500 minutes in bed, took 60 minutes to fall asleep, and had 60 minutes of wakefulness after sleep. Is this data valid?

Yes, the sleep diary entry is logically consistent.

Sleep efficiency is the ratio of total sleep time to the total time spent in bed, expressed as a percentage. The `calculate_sleep_metrics` tool handles this calculation automatically.

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