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SaaS KPI Economics

by rifatrahman414Updated May 4, 2026

Calculates SaaS unit economics metrics such as MRR bridge, LTV, CAC payback, runway, and 2D scenario grids using only user-supplied numerical inputs. No connections to Stripe or other external APIs in version 1. SaaS founders, finance analysts, and growth teams apply it to model business viability and forecast outcomes programmatically.

saas-metrics
unit-economics
financial-modeling
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Overview

SaaS KPI Economics is an MCP server that performs calculations for key SaaS unit economics metrics. It processes user-provided data to generate insights on MRR changes, customer lifetime value, customer acquisition cost recovery, financial runway, and multi-variable scenario analyses. All computations rely solely on inputs supplied by the user, ensuring data privacy and simplicity without external dependencies.

Key Capabilities

  • MRR bridge: Breaks down monthly recurring revenue changes into components like new sales, expansions, churn, and downgrades.
  • LTV: Computes lifetime value based on ARPU, gross margins, and retention/churn rates.
  • CAC payback: Determines months required to recover customer acquisition costs from LTV.
  • runway: Estimates cash burn duration using current cash, MRR, and expenses.
  • 2D scenario grids: Generates matrices of outcomes across two variables, such as churn vs. CAC, for sensitivity analysis.

Use Cases

  1. A SaaS founder inputs monthly MRR components to run an MRR bridge analysis, identifying churn as the primary growth blocker.
  2. Finance teams supply ARPU, margins, and retention data to calculate LTV and CAC payback, assessing pricing sustainability.
  3. During fundraising prep, operators model runway with cash reserves and burn rates to project survival months.
  4. Growth analysts create 2D scenario grids varying churn and expansion rates to visualize revenue projections under different conditions.

Who This Is For

Target users include SaaS founders needing quick financial modeling, CFOs and FP&A analysts evaluating unit economics, and growth managers simulating scenarios. It suits teams without dedicated modeling tools who require programmatic access via MCP for integration into workflows or AI agents.