# Emotional Variability Score MCP for AI Agents AI Agent Connect

> Emotional Variability Score MCP lets you turn raw mood data into actionable metrics. It quantifies how much your moods swing, identifies emotional extremes, and tracks stability trends over time. Use it to move past subjective feelings into hard data on mood amplitude and volatility.

## Overview
- **Category:** analytics
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_N7di3dkK2tDQPvgFYqqwRAYXn17N5jKOyGnRbZpR/ai-agent-connect
- **Tags:** mood, stability, volatility, emotion, metrics

## Description

This Connector lets you turn subjective feelings into measurable data points. If you're tracking mood, you know that feeling better isn't always a linear path. This tool gives you the math to back it up. You can look at the actual range between your highest and lowest points or see how often your mood shifts in a single week. It's designed for people who need to see the bigger picture of emotional stability, whether that's for personal research or building a wellness platform. By connecting this to your agent via the Vinkius catalog, you stop guessing about trends and start seeing the actual delta in your emotional volatility. You can pull a full report that summarizes everything, including stability status, range, and overall ratings, in one go. It's about getting a clear, data-driven view of emotional patterns without having to manually crunch numbers in a spreadsheet.

## Tools

### calculate_mood_amplitude
Finds the highest and lowest emotional points to show the total range of your moods. It identifies extremes for a period.

### calculate_instability_index
Calculates a score for how erratic or frequent your mood swings are in a specific window. It identifies the pattern type.

### get_comprehensive_emotional_report
Creates a high-level summary of all emotional metrics for a chosen period. It includes stability status and ratings.

### compare_weekly_volatility
Compares two consecutive weeks to show if emotional instability is getting better or worse. It provides a clear delta and trend.

## Prompt Examples

**Prompt:** 
```
How has my mood stability changed compared to last month?
```

**Response:** 
```
Based on your logs, here is the stability comparison:

| Metric | Last Month | This Month | Change |
| :--- | :--- | :--- | :--- |
| **Volatility** | 0.82 | 0.64 | -0.18 (Improving) |
| **Instability Index** | 4.2 | 3.1 | -1.1 |
| **Mood Range** | 8.5 | 6.2 | -2.3 |

Your mood swings are becoming less erratic, showing a clear trend toward stability.
```

**Prompt:** 
```
What were my highest and lowest points last week?
```

**Response:** 
```
Here are the extremes for last week:

*   **Peak Mood:** 9.2
*   **Valley Mood:** 3.4
*   **Total Range:** 5.8

Your highest point occurred on Wednesday, and your lowest was on Monday.
```

**Prompt:** 
```
Can you give me a summary of my emotional trends for November?
```

**Response:** 
```
### Emotional Summary: November

*   **Stability Status:** Stable
*   **Mood Amplitude:** 6.4
*   **Overall Rating:** 8/10

Your emotional range remained consistent throughout the month with a steady instability score, indicating a well-regulated mood state.
```

## Capabilities

### Track mood swing frequency
See how often your mood shifts over any selected date range.

### Identify emotional extremes
Get the specific peak and valley scores for a period.

### Measure weekly volatility
Compare two weeks to see if your stability is improving or worsening.

### Generate summary reports
Get an aggregated look at stability, range, and ratings.

### Quantify mood amplitude
Calculate the total range between your highest and lowest emotional states.

## Use Cases

### Tracking treatment progress
A researcher has 6 months of mood logs and needs to see if a new treatment is working. They ask the agent to use compare_weekly_volatility to track the trend across the first and last months.

### Identifying mood swing frequency
A user wants to know if their mood swings are becoming more frequent. They use calculate_instability_index to get a specific score for the last 30 days.

### Generating user dashboard data
A wellness app needs a summary for a user dashboard. The developer runs get_comprehensive_emotional_report to get a high-level rating of the user's stability.

### Analyzing stress impact
Someone wants to see the extremes of their emotions during a stressful work week. They use calculate_mood_amplitude to find the peak and valley scores for that specific week.

## Benefits

- Stop guessing about mood trends by using compare_weekly_volatility to see real week-over-week improvements.
- Identify your emotional floor and ceiling quickly with calculate_mood_amplitude to see the full range of your experience.
- Get a clear instability score for any date range using calculate_instability_index to see erratic patterns.
- Save time on manual reporting by pulling a full summary with get_comprehensive_emotional_report.
- Move from subjective descriptions to objective metrics for better personal or clinical insights.

## How It Works

The bottom line is you get a data-driven snapshot of emotional stability instead of just a list of feelings.

1. Connect your AI client to the Emotional Variability Score MCP through the Vinkius platform.
2. Provide the AI with your mood data or a specific date range you want to analyze.
3. Get a structured breakdown of instability scores, volatility trends, and summary reports.

## Frequently Asked Questions

**Can I use Emotional Variability Score to see if my mood swings are getting better?**
Yes, you can use the Connector to compare two different weeks. It will give you a clear delta and trend to show if your stability is improving or worsening over time.

**How does the Emotional Variability Score MCP measure mood extremes?**
It identifies your peak and valley scores for any period you choose. This helps you see the full range of your emotional experience, not just the average.

**What kind of data does the Emotional Variability Score MCP need?**
It works with mood logs, ratings, or any numerical representation of your emotional state. Your AI agent can then use these to calculate instability scores and volatility.

**Can I get a high-level summary of my emotional health?**
Yes, the Connector can generate a comprehensive report. It aggregates your data into a summary that includes your overall stability status, mood range, and a general rating.

**Is the Emotional Variability Score MCP good for tracking long-term trends?**
It is perfect for that. By using the volatility and instability tools, you can track how your emotional patterns shift over weeks or months.

**How does this help with mental health research?**
It allows researchers to move beyond qualitative descriptions. You can get specific metrics like the instability index to quantify how erratic mood swings are within specific date ranges.

**What does the instability index measure?**
The `calculate_instability_index` tool measures how frequently your mood changes direction, providing a score that represents the frequency of transitions between different emotional states.

**How is amplitude calculated?**
The `calculate_mood_amplitude` tool calculates the vertical distance between the highest (peak) and lowest (valley) mood scores recorded during your specified timeframe.

**Can I compare two different weeks?**
Yes, use the `compare_weekly_volatility` tool by providing the start dates for both the current and previous weeks to see if your emotional stability is trending up or down.