A Claude Code plugin marketplace for marimo reactive notebook tools and skills.
This marketplace provides curated plugins and skills for creating and editing marimo reactive notebooks with Claude Code. It helps you build efficient data science and analytics workflows using marimo's reactive programming model.
Note: Most of the prompts and instructions used in these plugins are transplanted from the original marimo prompts. This project inherits the Apache 2.0 License from marimo.
Create and edit marimo reactive notebooks with best practices.
Features:
- Create new marimo notebooks
- Convert Jupyter notebooks to marimo
- Implement reactive patterns and UI components
- Build interactive data visualizations
- Generate code following marimo best practices
Key capabilities:
- Understanding marimo's reactive programming model
- Proper use of UI elements
- Data handling best practices
- Integration with visualization libraries (matplotlib, plotly, altair)
- SQL (DuckDB) support
# Add the cc-marimo marketplace
/plugin marketplace add dakesan/marimo-cc# Install the marimo-editor plugin
/plugin install marimo-editor@cc-marimo# Clone the repository
git clone https://github.com/dakesan/marimo-cc.git
# Add as a local marketplace
/plugin marketplace add ./marimo-cc
# Install a plugin from local marketplace
/plugin install marimo-editor@cc-marimoAfter adding the marketplace and installing a plugin, it will automatically activate when you make requests like:
- "Create a marimo notebook"
- "Convert this Jupyter notebook to marimo"
- "Build an interactive visualization with marimo"
- "Add a slider to make this parameter adjustable with marimo"
User: "Create a marimo notebook to visualize the iris dataset"
Claude: I'll use the marimo-editor skill to create an interactive visualization notebook...
# Cell 1: Import libraries
import marimo as mo
import matplotlib.pyplot as plt
import numpy as np
# Cell 2: Create UI element
n_points = mo.ui.slider(10, 100, value=50, label="Number of points")
n_points
# Cell 3: Reactive visualization
x = np.random.rand(n_points.value)
y = np.random.rand(n_points.value)
plt.scatter(x, y)
plt.gca()marimo-cc/
├── .claude-plugin/
│ └── marketplace.json # Marketplace definition
├── plugins/
│ └── marimo-editor/
│ ├── .claude-plugin/
│ │ └── plugin.json # Plugin manifest
│ └── skills/
│ └── marimo-editor/
│ └── SKILL.md # Skill definition
├── LICENSE
└── README.md
- marimo must be installed
pip install marimo
# or
uv pip install marimoPull requests and issues are welcome! If you'd like to add more plugins to this marketplace:
- Create a new directory under
plugins/ - Add your plugin with proper
.claude-plugin/plugin.json - Update
.claude-plugin/marketplace.jsonto include your plugin - Submit a pull request
Apache License 2.0
This project is derived from marimo and inherits its Apache 2.0 License. Most of the prompts and instructions are transplanted from the original marimo project.
See LICENSE for details.
Hiroyuki Odake (@dakesan)
- marimo Official Site
- marimo Documentation
- marimo GitHub
- Claude Code Documentation
- This Marketplace Repository
Special thanks to the marimo team for creating marimo and providing the original prompts and instructions that this marketplace is based on.