# Emotional Regulation Scoring Engine AI Agent Connect

> Emotional Regulation Scoring Engine uses the Difficulties in Emotion Regulation Scale (DERS) to quantify psychological dimensions. Your AI client can process raw scale inputs to calculate total and subdomain scores, compare results against clinical benchmarks, and generate specific behavioral strategies based on the resulting profiles.

## Overview
- **Category:** analytics
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_nIFUCpTvIn5pFD9vTLbMWwzIHdFc0eOmckDuBcHp/ai-agent-connect
- **Tags:** emotional-intelligence, ders, psychology, scoring, behavioral-health

## Description

You can use this MCP to bring precise psychological measurement to your AI-driven workflows. It centers on the DERS framework, which breaks down emotional regulation into six specific areas: Emotional Awareness, Emotional Clarity, Emotion Regulation Strategies, Impulse Control, Goal-Directed Behavior, and Non-acceptance of Emotional Responses. Instead of guessing how a user is managing their emotions, your agent can process raw data to get hard numbers. You can check if inputs follow the required scale structure, pull clinical thresholds to see where a score sits on the spectrum, and immediately get behavioral recommendations based on the findings. It's a specialized tool for anyone needing to turn qualitative emotional data into quantitative insights without manual calculation.

## Tools

### get_thresholds
This tool provides the clinical or normative benchmarks needed to interpret scores. Use it to find specific thresholds for total scores or individual subdomains.

### validate_format
This tool checks if a set of user inputs matches the required scale structure. It ensures your data is valid before you attempt any calculations.

### calculate_ders_scores
This tool computes both total and subdomain scores from raw scale responses. It handles the math for the entire DERS framework.

### generate_recommendations
This tool produces actionable behavioral advice. It looks at the calculated score profiles to suggest specific strategies.

## Prompt Examples

**Prompt:** 
```
Calculate my emotional regulation scores for these responses: [3, 2, 4, 1, 5, 2, 3, 4, 1, 2, 3, 4, 5, 2]
```

**Response:** 
```
Your total score is 42. Your strongest area is Impulse Control, while your highest difficulty is in Non-acceptance of Emotional Responses.
```

**Prompt:** 
```
What are the clinical thresholds for the total score?
```

**Response:** 
```
For the total score, low difficulty is below 30, moderate difficulty is between 30 and 45, and high difficulty is above 45.
```

**Prompt:** 
```
Check if my input format is correct: [1, 2, 3]
```

**Response:** 
```
The input is invalid. The DERS scale requires exactly 14 integer responses.
```

## Capabilities

### DERS Scoring
Your agent calculates total and subdomain scores from raw user inputs.

### Clinical Benchmarking
The AI compares calculated scores against established clinical thresholds.

### Behavioral Strategy Generation
Your agent produces specific behavioral advice based on a user's score profile.

### Input Validation
The MCP verifies that raw data matches the required DERS scale structure.

## Use Cases

### Automated Patient Assessment
An agent processes a patient's completed DERS scale to identify specific areas of emotional difficulty.

### Research Data Processing
Researchers use the tool to quickly calculate scores for multiple participants in a study.

### Clinical Decision Support
Clinicians use the thresholds to determine if a patient's score falls into low, moderate, or high difficulty categories.

### Behavioral Strategy Planning
The AI generates personalized advice based on a user's unique emotional regulation profile.

## Benefits

- Automates the math for the six DERS subdomains.
- Provides instant comparison against clinical benchmarks.
- Converts raw numbers into specific behavioral recommendations.
- Validates data integrity before processing scores.

## How It Works

Connect the MCP to your client and start sending data for analysis.

1. Connect the MCP to your preferred client like Claude or Cursor.
2. Provide raw scale responses to the agent.
3. The agent validates the input format to ensure it is correct.
4. The MCP calculates the total and subdomain scores.
5. The agent compares scores to thresholds and generates recommendations.

## Frequently Asked Questions

**What framework does this MCP use?**
This MCP uses the Difficulties in Emotion Regulation Scale (DERS) to quantify emotional regulation across six dimensions.

**How many responses are needed for a valid score?**
The DERS scale requires exactly 14 integer responses to be valid.

**Can I get specific advice based on my scores?**
Yes, the generate_recommendations tool provides actionable behavioral advice based on your calculated score profiles.

**What are the difficulty levels for total scores?**
Low difficulty is below 30, moderate difficulty is between 30 and 45, and high difficulty is above 45.

**Which AI clients can use this MCP?**
You can use this MCP with any MCP-compatible client, including Claude, Cursor, and Windsurf.