FinanceToolkit is a Python library for financial analysis that implements over 500 financial calculation methods with complete transparency of their underlying formulas.
The project addresses the problem of inconsistent financial metrics across data providers, where the same metric can vary significantly depending on the calculation methodology used. Rather than relying on opaque third-party sources, FinanceToolkit provides open-source implementations of financial methods written in the simplest possible way, with all formulas visible in the codebase. This allows analysts to understand exactly how each metric is calculated and to apply consistent definitions across their analysis. The toolkit supports a broad range of asset classes including equities, options, currencies, cryptocurrencies, ETFs, mutual funds, indices, commodities, and economic indicators, enabling both historical data retrieval and performance measurements like Sharpe Ratio and Value at Risk.
Developers should choose this tool if they need transparent, reproducible financial calculations without dependency on proprietary metric providers. It suits projects requiring consistent methodology across multiple assets or competitive analysis workflows, particularly when combined with the companion Finance Database for symbol lookup. The project is available both as a Python library and as an MCP Server, allowing integration with AI assistants like Claude and Copilot without writing code.
The project maintains active development with regular updates to its calculation methods and asset class support. The codebase demonstrates a commitment to methodological clarity through extensive inline documentation and formula visibility. The toolkit has expanded its accessibility by offering both local and hosted MCP Server deployment options, enabling integration across multiple AI platforms and client applications.
