mcdcf.com

What It Is

MCDCF (Monte Carlo Discounted Cash Flow) is a discounted cash flow simulation tool for real estate investment analysis. Instead of producing a single deterministic forecast, it uses the Monte Carlo method to generate distributions of future cash flows and investment performance metrics. Key outputs include NPV, IRR, before-tax cash flow (BTCF), after-tax cash flow (ATCF), NOI, and more. It is well suited to evaluating the risks and returns of property investments under changing assumptions for inflation, economic growth, interest rates, rent, occupancy, and expenses.

Core Features and Modeling Capabilities

The tool covers modules such as economic and model parameters, property details, income, operating expenses, capital expenditures, and taxes. Economic growth, inflation, and discount rates can be configured as fixed values, sampled values, one-time samples, or tabular sequences. Income and occupancy can be modeled as fixed, Sample, Random Walk, Tabular, or linked to changes in inflation or economic growth. Expenses can be entered either as absolute amounts or calculated as a percentage of income. The debt module includes principal, term, interest rate, and amortization period, while the tax module covers depreciation, marginal tax rate, capital gains tax, and depreciation recapture tax. Overall, the model is fairly granular and is especially useful for real estate cash flow sensitivity analysis.

Data, Export, and Integration

MCDCF supports printing or saving to PDF via Ctrl+P, making it convenient for generating investment reports. Project configurations can be compressed into URL parameters for sharing, with the documentation explicitly stating that there is “no server involved, full project encoded in URL.” It also supports import and export of uncompressed JSON configurations and provides sample JSON that can be used with LLMs. This is helpful for reusing scenarios, preserving versions, and using large language models to generate initial models. However, the documentation does not mention APIs, SDKs, plugins, or integrations with Excel, BI tools, accounting systems, or other third-party platforms.

Pricing, Deployment, and Documentation

The documentation does not disclose pricing, payment methods, or commercial support. It provides a bundled offline version via GitHub releases, indicating that offline use is supported, but it does not clearly state the license, whether it is fully open source, or whether formal self-hosting is supported. The documentation quality is good: fields, variation methods, and example configurations for each module are explained in sufficient detail, allowing users to understand the model structure.

Pros, Cons, and Best-Fit Users

Its strengths include comprehensive real estate DCF modeling dimensions, probabilistic simulation, offline availability, and URL/JSON-based sharing. Its weaknesses are limited developer ecosystem information, lack of API/SDK details, missing pricing and service support information, and tax examples that are somewhat U.S.-centric. It is better suited to real estate investors, asset managers, and financial analysts than to general software development teams.

Access from China

Based on the available documentation, it is not possible to determine how reliably mcdcf.com can be accessed from mainland China. Downloads from GitHub releases may also be affected by local network conditions. If access is restricted, users can consider using the offline version, or alternatives such as Excel/Google Sheets, Python financial models, or real estate DCF templates.