# Customer Health Score AI Agent Connect

> Customer Health Score MCP lets your AI client monitor the entire customer lifecycle. It pulls together usage frequency, feature adoption, support tickets, and payment history to build a clear picture of account stability. You can use it to spot churn risks before they happen or identify which customers are ready for an upsell.

## Overview
- **Category:** customer-success
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_SNzf4XX4BqKpVfzd9BWUsGQTS6J4J8sKYPTAaFCk/ai-agent-connect
- **Tags:** churn-prediction, customer-health, retention, usage-analytics, nps

## Description

You can stop guessing which accounts are at risk. This MCP gives your AI agent direct access to the metrics that actually matter for retention. Instead of digging through separate dashboards for usage, billing, and support, you can ask your AI client to aggregate everything into a single health profile. 

It looks at how deeply customers use your product through adoption metrics and checks their financial stability via payment history. It also monitors sentiment by looking at support engagement and NPS trends. By comparing individual accounts against segment benchmarks, your agent can tell you if a customer is lagging behind their peers or if they are a prime candidate for expansion. It turns raw data into a predictable roadmap for your customer success efforts.

## Tools

### analyze_usage_and_adoption
This tool measures how deeply a customer has integrated your product into their daily workflow. It tracks feature adoption to see if they are getting real value.

### assess_financial_health
This tool checks the stability of the relationship by looking at payment history. It helps identify billing issues that might signal future churn.

### compare_to_segment_benchmarks
This tool compares a specific customer's metrics against their peer group. It shows you if an account is performing better or worse than similar users.

### evaluate_sentiment_and_support
This tool assesses customer satisfaction and friction. It looks at support engagement and sentiment trends to find unhappy users.

### get_customer_health_score
This tool pulls a complete health profile for a specific customer. It provides a high level overview of their current status.

## Prompt Examples

**Prompt:** 
```
What is the current health status of customer CUST-123?
```

**Response:** 
```
Customer CUST-123 has a health score of 85, which is considered Healthy. The churn risk is Low, and there is a High expansion opportunity.
```

**Prompt:** 
```
How is the feature adoption for customer CUST-456?
```

**Response:** 
```
Customer CUST-456 has a feature adoption percentage of 78% and is currently in a High engagement status.
```

**Prompt:** 
```
Is customer CUST-789's sentiment improving?
```

**Response:** 
```
The sentiment trend for CUST-789 is positive, with an NPS score of 45 and a decreasing volume of support tickets.
```

## Capabilities

### Churn Prediction
Your agent identifies accounts showing signs of declining usage or sentiment.

### Expansion Identification
The AI finds customers with high health scores who are ready for upsells.

### Usage Monitoring
Your client tracks how features are being adopted across your user base.

### Financial Oversight
The tool monitors payment history to flag potential billing churn.

### Benchmarking
Your agent compares individual account performance against specific peer segments.

## Use Cases

### Proactive Churn Prevention
Your agent flags a customer whose usage has dropped and sentiment is trending down.

### Upsell Targeting
You ask your AI to find customers with high health scores and high feature adoption for expansion.

### Segment Analysis
You compare a new cohort's health against established benchmarks to see how they are performing.

### Support Friction Audit
You use sentiment analysis to find customers struggling with specific product features.

## Benefits

- Reduces churn by flagging declining engagement early.
- Identifies upsell opportunities through high adoption signals.
- Centralizes usage, sentiment, and billing data for your AI agent.
- Provides peer comparisons to contextualize account performance.

## How It Works

Get your AI client working with your customer data in minutes.

1. Connect your preferred MCP client to Vinkius.
2. Select the Customer Health Score MCP from the catalog.
3. Your AI agent gains access to the health, usage, and financial tools.
4. Ask your agent questions about specific customers or segments to get instant answers.

## Frequently Asked Questions

**What AI clients can I use with this MCP?**
You can connect this MCP to any compatible client like Claude, Cursor, Windsurf, or VS Code.

**Do I need to host the MCP myself?**
No. Vinkius hosts and manages the MCP for you, so it is ready to use immediately after you connect.

**How does the health score get calculated?**
The score is generated by aggregating usage frequency, feature adoption, support engagement, NPS, and payment history.

**Can I use this to find upsell opportunities?**
Yes. You can use the tool to identify customers with high health scores and high feature adoption who are ready for expansion.

**Does this work with my existing customer data?**
This MCP is designed to pull from your customer lifecycle data to provide real time insights through your AI agent.