Mood Pattern Detector

Mood Pattern Detector MCP Connector for Claude

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Identify recurring emotional trends and correlations between mood fluctuations and lifestyle variables.

3 tools Official Updated Jun 28, 2026 Official Vinkius Partner

The Mood Pattern Detector analyzes historical mood logs to uncover cyclical patterns and the impact of external factors. Use analyze_weekly_cycle to find days associated with specific moods, evaluate_activity_impact to measure how variables like exercise or sleep influence your emotional state, and identify_mood_anomalies to flag significant deviations from your baseline mood.

moodpatternssentimentlifestyleanalytics

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

analyze_weekly_cycle

Determine if specific days of the week are associated with better or worse moods

evaluate_activity_impact

Measure how a specific recorded variable influences mood levels

identify_mood_anomalies

Flag specific dates where the mood was significantly different from the norm

See how to talk to your AI agent using Mood Pattern Detector.

Are there any specific days of the week where my mood tends to be lower?

The `analyze_weekly_cycle` tool would examine your logs and return the day with the lowest average mood score, such as identifying a 'Monday Slump'.

Does my exercise routine affect my emotional well-being?

By using `evaluate_activity_impact` with 'exercise' as the variable, the tool will compare your average mood on days you exercised versus days you did not.

Check if there were any unusual spikes or drops in my mood recently.

The `identify_mood_anomalies` tool will scan your historical data and list specific dates where your mood was significantly higher or lower than your norm.

The `analyze_weekly_pattern` tool calculates the average mood score for each day of the week present in your logs and identifies significant differences between days.

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