import-unit-economics-mcp
Imports unit economics data such as customer acquisition cost (CAC), lifetime value (LTV), and gross margins into model contexts via the MCP protocol. Developers and financial analysts use it to integrate business metrics into AI-driven analysis pipelines. Applications include profitability modeling for SaaS products and startup financial forecasting.
Overview
The import-unit-economics-mcp server enables the ingestion of unit economics data into AI model contexts through the Model Context Protocol (MCP). It handles structured data like CAC, LTV, contribution margins, and churn rates, allowing models to perform calculations and simulations without manual data entry.
Key Capabilities
No specific tools are listed in the current discovery. The server focuses on importing unit economics datasets, supporting formats common in financial spreadsheets (e.g., CSV, JSON) and mapping them to model-readable structures for queries on per-unit revenue, costs, and profitability.
Use Cases
-
SaaS Profitability Analysis: Import monthly CAC and LTV data to let models compute payback periods and predict scaling impacts.
-
Startup Valuation: Load unit metrics into valuation models to simulate growth scenarios based on real cohort data.
-
E-commerce Optimization: Ingest gross margin and fulfillment costs to optimize pricing strategies via AI recommendations.
-
Investor Reporting: Automate import of unit economics for generating dashboards on customer economics trends.
Who This Is For
Financial analysts tracking business metrics, developers building AI financial tools, startup operators modeling growth, and data scientists integrating economics data into ML workflows.