# Product-Market Fit Score Engine AI Agent Connect

> Quantify product-market fit using Sean Ellis methodology and business metrics.

## Overview
- **Category:** business-intelligence
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_oa3B2kvVFph49PCUm8EvG4f1fabP2Tzuq5Ta72qO/ai-agent-connect
- **Tags:** pmf, product-metrics, sean-ellis, growth, retention

## Description

This MCP server provides a diagnostic engine to quantify Product-Market Fit (PMF). It synthesizes qualitative user sentiment from the Sean Ellis test with quantitative business health metrics like retention and organic growth. Use `calculate_sentiment_metrics` to analyze survey responses, `calculate_pmf_composite_score` to generate a 0-100 index, `analyze_cohort_variance` to adjust for early adopter bias, and `get_market_readiness_guidance` to receive actionable business directions.

## Tools

### calculate_sentiment_metrics
Analyzes raw survey responses to determine the qualitative health of the product

### analyze_cohort_variance
Adjusts the PMF score to account for potential bias between early adopters and the broader market

### calculate_pmf_composite_score
Generates the final 0-100 PMF score by combining qualitative sentiment and quantitative business metrics

### get_market_readiness_guidance
Translates the PMF score and readiness level into actionable business directions

## Prompt Examples

**Prompt:** 
```
Analyze these survey responses: ['very disappointed', 'somewhat disappointed', 'very disappointed', 'not disappointed'].
```

**Response:** 
```
The very disappointed percentage is 50% with a total of 4 responses.
```

**Prompt:** 
```
Calculate the PMF score with 40% very disappointed, 30 NPS, 45% retention, and 15% organic growth.
```

**Response:** 
```
The calculated PMF score is 65, indicating an Optimization readiness level.
```

**Prompt:** 
```
What is the recommended action for a PMF score of 85 and 20% retention?
```

**Response:** 
```
The primary focus should be on Product Stability due to the high score paired with low retention.
```

## Frequently Asked Questions

**What is the Sean Ellis test?**
It is a qualitative survey method that asks users how they would feel if they could no longer use the product, identifying the 'very disappointed' segment.

**How is the PMF score calculated?**
The score is a weighted composite index combining the 'very disappointed' percentage with NPS, retention rate, and organic growth.

**Can I adjust for early adopter bias?**
Yes, use `analyze_cohort_variance` to adjust the score based on cohort age and sample size to account for potential over-reporting of satisfaction.