A meta-tool for setting up Poetry-based Python projects with configurable presets
Project description
pypreset
mcp-name: io.github.KaiErikNiermann/pypreset
A meta-tool for scaffolding Python projects with configurable YAML presets. Supports Poetry and uv, generates CI workflows, testing scaffolds, type checking configs, and more.
Features
- Preset-based project creation from YAML configs with single inheritance
- Augment existing projects with GitHub Actions workflows, tests, dependabot,
.gitignore - Two package managers: Poetry and uv (PEP 621 + hatchling)
- Two layout styles:
src/layout and flat layout - Type checking: mypy, pyright, ty, or none
- Code quality: ruff linting/formatting, radon complexity checks, pre-commit hooks
- Version management: bump-my-version integration, GitHub release automation via
ghCLI - User defaults: persistent config at
~/.config/pypreset/config.yaml - MCP server: expose all functionality to AI coding assistants via Model Context Protocol
Installation
# Core CLI
poetry install
# With MCP server support
poetry install -E mcp
Quick Start
# Create a CLI tool project with Poetry
pypreset create my-cli --preset cli-tool
# Create a data science project with uv
pypreset create my-analysis --preset data-science --package-manager uv
# Create an empty package with src layout (default)
pypreset create my-package --preset empty-package
# Create a Discord bot
pypreset create my-bot --preset discord-bot
Commands
create — Scaffold a new project
pypreset create <name> [OPTIONS]
| Option | Description |
|---|---|
--preset, -p |
Preset to use (default: empty-package) |
--output, -o |
Output directory (default: .) |
--config, -c |
Custom preset YAML file |
--package-manager |
poetry or uv |
--layout |
src or flat |
--type-checker |
mypy, pyright, ty, or none |
--typing |
none, basic, or strict |
--python-version |
e.g., 3.12 |
--testing / --no-testing |
Enable/disable testing scaffold |
--formatting / --no-formatting |
Enable/disable formatting config |
--radon / --no-radon |
Enable radon complexity checking |
--pre-commit / --no-pre-commit |
Generate pre-commit hooks config |
--bump-my-version / --no-bump-my-version |
Include bump-my-version config |
--extra-package, -e |
Additional packages (repeatable) |
--extra-dev-package, -d |
Additional dev packages (repeatable) |
--git / --no-git |
Initialize git repository |
--install / --no-install |
Run dependency install after creation |
augment — Add components to an existing project
Analyzes pyproject.toml to auto-detect your tooling, then generates the selected components.
# Interactive mode (prompts for missing values)
pypreset augment ./my-project
# Auto-detect everything, no prompts
pypreset augment --auto
# Generate only specific components
pypreset augment --test-workflow --lint-workflow --gitignore
# Overwrite existing files
pypreset augment --force
version — Release management
pypreset version release <bump> # Bump, commit, tag, push, release
pypreset version release-version <ver> # Explicit version, then release
pypreset version rerun <ver> # Re-tag and push an existing version
pypreset version rerelease <ver> # Delete and recreate a GitHub release
Requires the gh CLI to be installed and authenticated.
Other commands
pypreset list-presets # List all available presets
pypreset show-preset <name> # Show full preset details
pypreset validate [path] # Validate project structure
pypreset analyze [path] # Detect and display project tooling
pypreset config show # Show current user defaults
pypreset config init # Create default config file
pypreset config set <key> <value> # Set a config value
Presets
Built-in presets: empty-package, cli-tool, data-science, discord-bot.
Presets are YAML files that define metadata, dependencies, directory structure, testing, formatting, and more. They support single inheritance via the base: field.
Custom presets
Place custom preset files in ~/.config/pypreset/presets/ or pass a file directly:
pypreset create my-project --config ./my-preset.yaml
User presets take precedence over built-in presets with the same name.
User Configuration
Persistent defaults are stored at ~/.config/pypreset/config.yaml and applied as the lowest-priority layer (presets and CLI flags override them).
pypreset config init # Create with defaults
pypreset config set layout flat # Set default layout
pypreset config set type_checker ty # Set default type checker
pypreset config show # View current config
MCP Server
An MCP (Model Context Protocol) server exposes pypreset to AI coding assistants over STDIO.
# Run the server
pypreset-mcp
Add to Claude Code settings.json:
{
"mcpServers": {
"pypreset": {
"command": "pypreset-mcp",
"args": []
}
}
}
Available tools: create_project, augment_project, validate_project, list_presets, show_preset, get_user_config, set_user_config
Resources: preset://list, config://user, template://list
Prompts: create-project, augment-project
Development
All tasks use the Justfile:
just install # Install dependencies
just test # Run tests
just test-cov # Tests with coverage
just lint # Ruff check
just format # Ruff format
just typecheck # Pyright
just radon # Cyclomatic complexity check
just check # lint + typecheck + radon + test
just all # format + lint-fix + typecheck + radon + test
See CONTRIBUTING.md for development setup and guidelines.
License
MIT
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refs/tags/v0.1.4 - Owner: https://github.com/KaiErikNiermann
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