MCP For Claude Marketplace
Infra Revenue Volatility Score

Infra Revenue Volatility Score MCP Connector for Claude

A+

Quantifies infrastructure revenue stability and predictability.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides a specialized analysis engine to quantify the stability and predictability of infrastructure-related revenue. It evaluates historical fluctuations, seasonal trends, and contractual risk factors to produce actionable metrics. Use get_volatility_metrics to assess overall risk, analyze_contractual_stability to evaluate contract impact, evaluate_seasonal_impact to distinguish seasonal patterns from true instability, and forecast_revenue_confidence to predict future revenue reliability.

revenuevolatilityforecastingpredictabilityrisk-analysis

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

analyze_contractual_stability

Determines how much the specific contract types contribute to or detract from revenue predictability

evaluate_seasonal_impact

Distinguishes between random volatility and predictable seasonal fluctuations

forecast_revenue_confidence

Predicts the reliability of future revenue based on current trends and risks

get_volatility_metrics

Provides a high-level summary of the current revenue stability and risk profile

See how to talk to your AI agent using Infra Revenue Volatility Score.

What is our current revenue stability profile based on these monthly revenues: [10000, 12000, 11000, 10500] and a churn rate of 0.05?

The current volatility score is 2.5, indicating high stability, with a predictability index of 92% and a Low risk level.

How much do our contract types affect revenue predictability?

The stability impact score is high due to the prevalence of fixed-term contracts, though there is a moderate renewal risk factor clustered in Q3.

Is the recent revenue dip a seasonal pattern or true instability?

The fluctuation aligns with the provided Q4 spike pattern, so the volatility is considered expected seasonal variance rather than true instability.

It is a normalized metric from 1 to 10 that quantifies revenue fluctuations. You can obtain this using the `get_volatility_metrics` tool.

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