Cursor MDC Generator automates the creation of documentation files for the Cursor IDE by analyzing the structure and dependencies of repositories. Supporting local and remote repositories across various programming languages, it simplifies documentation generation with easy installation and usage instructions.
Cursor MDC Generator is a powerful tool designed to facilitate the generation of Cursor IDE documentation files (MDC) through comprehensive analysis of repositories. This utility efficiently automates the documentation process, allowing developers to focus on coding rather than manual documentation tasks.
To utilize the Cursor MDC Generator for different scenarios, several commands are available:
# Analyze the current directory
mdcgen
# Analyze a specific local directory
mdcgen /path/to/repository
# Analyze a remote GitHub repository
mdcgen --repo https://github.com/user/repo
# Specify an output directory for generated MDC files
mdcgen /path/to/repository --out ./mdc-output
# Use a specific model for summaries
mdcgen /path/to/repo --model gpt-4o
# Skip visualization if Graphviz is not installed
mdcgen /path/to/repo --no-viz
For private repositories, authentication is simple:
mdcgen --repo https://github.com/user/private-repo --token YOUR_GITHUB_TOKEN
A set of options is available to customize the analysis:
| Option | Alias | Description |
|---|---|---|
PATH | Local path to repository (default: current directory) | |
--repo | -r | GitHub repository URL (instead of local path) |
--out | -o | Output directory for analysis files |
--model | -m | Model to use for summaries (default: gpt-4o-mini) |
--token | -t | OAuth token for private repositories |
--imports | -i | Include @file references to imported files |
--no-viz | Skip generating dependency graph visualizations | |
--no-dirs | Skip generating directory-level MDC files | |
--depth | -d | Max directory depth (0=repo only, 1=top-level dirs) |
--log-level | Set logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL) |
With these functionalities, Cursor MDC Generator enhances the efficiency of documentation production, providing a structured approach that is both scalable and user-friendly.
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