MCP For Claude Marketplace
Enterprise Feature Adoption Depth

Enterprise Feature Adoption Depth MCP Connector for Claude

A+

Quantify customer integration, stickiness, and expansion opportunities.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides a sophisticated analytics engine to measure how deeply enterprise customers integrate product features into their workflows. It calculates adoption depth scores, identifies feature stickiness to predict churn, and uncovers expansion opportunities by mapping usage to business use cases. Use calculate_adoption_depth to measure integration, analyze_feature_stickiness to assess churn risk, identify_expansion_opportunities for upsell targets, and evaluate_training_efficacy to determine if low usage stems from training gaps or product friction.

adoptionchurn-predictionupsellcustomer-successproduct-analytics

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

analyze_feature_stickiness

Analyzes the strength of a customer's attachment to specific features

calculate_adoption_depth

Calculates how deeply a customer is integrated into the product ecosystem

evaluate_training_efficacy

Evaluates whether low adoption is due to user ignorance or product friction

identify_expansion_opportunities

Identifies potential features for sales or success teams to pitch to a customer

See how to talk to your AI agent using Enterprise Feature Adoption Depth.

How deeply is our current enterprise client integrated into the platform?

The customer has an adoption depth score of 0.85, indicating high integration due to frequent use of core feature combinations.

Is this customer at risk of churning?

The churn risk level is Stable, as the user is currently utilizing key feature dependencies.

What features should we recommend to increase this account's value?

Based on the current use case alignment, we recommend pitching the Advanced Reporting and Automated Workflows features.

By using `analyze_feature_stickiness`, you can identify if a customer is utilizing core feature combinations that create high value, which is a strong indicator of retention.

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