# Burnout Detector MCP for AI Agents AI Agent Connect

> Burnout Detector MCP lets your AI agent analyze survey data against the Maslach Burnout Inventory (MBI) model. It identifies specific risk levels for emotional exhaustion, depersonalization, and personal accomplishment. Use it to turn raw numbers into actionable insights about team well-being or individual stress.

## Overview
- **Category:** productivity
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_9v6zwnwwIEQhxPOsC74bjZ4NMIr76DDotkCET3qn/ai-agent-connect
- **Tags:** burnout, mbi, mental-health, assessment, diagnostic

## Description

Burnout Detector lets you move past vague feelings of "low morale" and into actual, standardized data. If you're trying to track team health or personal well-being, guessing is a losing game. This Connector takes the guesswork out of identifying burnout by applying the Maslach Burnout Inventory standard directly to your data. Instead of seeing a pile of survey comments, you can feed raw scores into your AI agent to get a clear picture of where the cracks are forming. It breaks things down into three core buckets: how drained people feel, how detached they've become from their work, and whether they still feel like they're actually achieving anything. It's a way to move from "I think people are tired" to "This specific team is hitting a severe exhaustion threshold." By connecting this through Vinkius, you give your AI client a professional diagnostic lens to spot risks before they turn into resignations or total crashes. It's about getting a standard score that actually means something in a clinical or organizational context.

## Tools

### calculate_burnout_metrics
Converts raw survey scores into standardized burnout metrics. It helps your agent interpret numerical data correctly.

### get_dimension_health_status
Checks the health of one specific burnout dimension at a time. This lets you see exactly where the problem lies.

### evaluate_risk_level
Calculates the overall burnout risk level based on all metrics. It gives you a clear Low to Severe rating.

## Prompt Examples

**Prompt:** 
```
Check the risk level for a team that scored 90 on exhaustion, 80 on depersonalization, and 10 on accomplishment.
```

**Response:** 
```
### Burnout Risk Assessment

| Dimension | Score | Status |
| :--- | :--- | :--- |
| Emotional Exhaustion | 90 | **Critical** |
| Depersonalization | 80 | **High** |
| Personal Accomplishment | 10 | **Very Low** |

**Overall Risk Level: Severe**

This team is showing extreme signs of burnout. The combination of high exhaustion and very low accomplishment suggests a high risk of immediate turnover or total crash.
```

**Prompt:** 
```
Calculate the burnout metrics for these scores: Exhaustion [70, 80], Depersonalization [60, 65], Accomplishment [85, 90].
```

**Response:** 
```
### Calculated Burnout Metrics

*   **Emotional Exhaustion:** 75.0
*   **Depersonalization:** 62.5
*   **Personal Accomplishment:** 87.5

These metrics provide a baseline for the team's current well-being status.
```

**Prompt:** 
```
What's the health status for 'Personal Accomplishment' if the score is 90?
```

**Response:** 
```
### Dimension Health Status

*   **Dimension:** Personal Accomplishment
*   **Score:** 90
*   **Status:** **Stable**

This represents a positive trend in professional well-being. The individual feels effective and capable in their current role.
```

## Capabilities

### Turn survey scores into MBI metrics
The agent converts raw numbers into standardized burnout dimensions automatically.

### Check specific dimension health
See exactly which area is failing, like depersonalization or lack of accomplishment.

### Get risk level ratings
Get a clear classification from Low to Severe based on the data provided.

### Identify emotional exhaustion
Quantify how drained your team members feel on a standardized scale.

### Spot depersonalization trends
Detect when people are becoming emotionally detached from their professional roles.

### Track personal accomplishment
Monitor whether employees still feel they are making progress in their work.

## Use Cases

### Prioritizing high-risk departments
HR has 500 survey responses and doesn't know which departments to prioritize. The agent uses calculate_burnout_metrics to rank every department by risk.

### Diagnosing employee detachment
A manager feels a team is checked out. The agent uses get_dimension_health_status to see if it's depersonalization or just low accomplishment.

### Quick wellness pulse checks
A wellness coach needs a quick pulse check for a client. The coach asks the agent to evaluate a client's risk level using evaluate_risk_level.

### Tracking remote team trends
Identifying trends in a remote team. The agent analyzes scores over time to see if exhaustion is trending upward across the company.

## Benefits

- Stop guessing about team morale by using the Maslach Burnout Inventory standard via calculate_burnout_metrics.
- Identify specific risk tiers from Low to Severe instantly using evaluate_risk_level.
- Pinpoint exactly which area is failing, like depersonalization, with get_dimension_health_status.
- Turn messy survey data into clean, professional reports for HR presentations.
- Spot early warning signs of exhaustion before they lead to actual turnover.
- Maintain a consistent diagnostic framework across different departments or teams.

## How It Works

The bottom line is you get a standardized burnout risk score instead of just a pile of survey comments.

1. Input raw survey scores for exhaustion, depersonalization, and accomplishment into your AI client.
2. The Connector processes these scores against the Maslach Burnout Inventory framework.
3. Your agent provides a clear risk tier and a breakdown of specific health statuses.

## Frequently Asked Questions

**What is the Burnout Detector MCP?**
It is a tool that lets your AI agent analyze survey data using the Maslach Burnout Inventory standard. It helps you turn raw numbers into clear risk levels for your team.

**How does it use the MBI model?**
It applies the Maslach Burnout Inventory framework to your data to check three specific areas: exhaustion, depersonalization, and personal accomplishment.

**Can it help identify high-risk employees?**
Yes, it provides a risk tier from Low to Severe. This makes it easy to spot which individuals or departments need immediate attention.

**Does it work with my current survey data?**
If you have numerical scores from a survey, your AI agent can feed those into this Connector to get a professional assessment.

**What's the difference between the three dimensions?**
Exhaustion is about feeling drained, depersonalization is about feeling detached from work, and accomplishment is about feeling like you're actually making progress.

**How do I use it for team wellness?**
You can ask your AI agent to analyze your team's survey results to identify trends and risk levels, helping you create targeted wellness plans.

**Can I use it to track burnout over time?**
Yes, by feeding in scores from different periods, you can see if your team's risk level is improving or getting worse.

**What is the Burnout Detector?**
It is a diagnostic tool based on the Maslach Burnout Inventory (MBI) that evaluates emotional exhaustion, depersonalization, and personal accomplishment.

**How do I use the `calculate_burnout_metrics` tool?**
Provide arrays of numerical scores for exhaustion, depersonalization, and accomplishment. The tool will return the average score for each dimension and an overall burnout index.

**What does a 'High' risk level mean?**
A High risk level indicates that visible depletion and cynicism are present, which can significantly impact work quality.