MCP For Claude Marketplace
Product Usage & Engagement Engine

Product Usage & Engagement Engine MCP Connector for Claude

A+

Analyze product stickiness, engagement scores, and user retention correlations.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides a specialized suite of analytical tools to measure product health and user behavior. It connects your AI agents to deep engagement metrics, allowing for automated analysis of stickiness, user interaction depth, and retention patterns. Use get_stickiness_metrics to calculate the DAU/MAU ratio, calculate_engagement_score to synthesize user activity into a single health metric, analyze_retention_correlation to see if engagement drives longevity, and generate_power_user_distribution to identify your most active user segments.

engagementretentionmetricsproduct-healthuser-behavior

4 tools expose this connector's capabilities to your AI agent.

generate_power_user_distribution

Pass userActivityDays as a JSON string of per-user active-day arrays. Break the user base into activity tiers to reveal power-user density

analyze_retention_correlation

Pass engagementMetrics as a JSON string and the matching retentionRates array in the same order. Test whether higher engagement actually correlates with better retention

calculate_engagement_score

Supply average session duration, actions per session, and the feature adoption rate (0 to 1). Roll session depth and feature adoption into one engagement score

get_stickiness_metrics

Supply the daily and monthly active user counts; the ratio nears 1 when users return every day. Compute the DAU/MAU stickiness ratio — how often monthly users return daily

See how to talk to your AI agent using Product Usage & Engagement Engine.

What is the stickiness ratio for a product with 500 DAU and 5000 MAU?

The stickiness ratio is 0.1, which represents a 10% stickiness level.

Calculate the engagement score for a session lasting 15 minutes with 20 actions and a 0.5 feature adoption rate.

The synthesized engagement score is 75, which falls into the High Engagement category.

Analyze the correlation between these engagement scores [0.8, 0.6, 0.4] and retention rates [0.5, 0.3, 0.1].

The correlation coefficient is 1.0, indicating a Strong and statistically significant relationship between engagement and retention.

You can use the `get_stickiness_metrics` tool by providing your Daily Active Users (DAU) and Monthly Active Users (MAU).

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