MCP For Claude Marketplace
Enterprise Churn Analyzer

Enterprise Churn Analyzer MCP Connector for Claude

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Analyze churn rates, revenue impact, and risk indicators across enterprise customer tiers.

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

This MCP server provides deep visibility into customer attrition by segmenting data into distinct business tiers. It allows AI agents to distinguish between logo churn (customer count) and revenue churn (ARR impact), which is critical for identifying whether small customers or high-value 'whales' are leaving. Use get_tier_summary to view high-level metrics, get_churn_reason_distribution to identify why customers leave, analyze_risk_indicators to detect dangerous churn patterns, and compare_tiers_performance to evaluate volatility between different segments.

churnrevenueenterprisemetricssaas-analytics

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

analyze_risk_indicators

Evaluates whether a tier is experiencing "dangerous" churn patterns based on revenue and logo correlations

compare_tiers_performance

Compares key churn metrics across two different tiers to identify disproportionate loss

get_churn_reason_distribution

Identifies the most common reasons why customers are leaving within a specific tier

get_tier_summary

Provides a high-level overview of churn metrics for a specific customer tier

See how to talk to your AI agent using Enterprise Churn Analyzer.

What is the current churn status for the Enterprise tier?

The Enterprise tier currently has a logo churn rate of 2% and a revenue churn rate of 8%, indicating a high risk due to high-value customer loss.

Why are customers in the Mid-Market tier leaving?

The primary reasons for churn in the Mid-Market tier are pricing competition (45%) and product feature gaps (30%).

Compare the churn performance between SMB and Enterprise tiers.

The SMB tier has a higher logo churn delta, while the Enterprise tier shows a significantly higher revenue impact ratio.

By using `analyze_risk_indicators`, you can detect if revenue churn is significantly higher than logo churn, which signals that high-value customers are leaving.

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