plotly

Q: How to install plotly?

Open your MCP config: ~/.claude.json. Then add the config to "mcpServers": { "plotly": { "command": "...", "args": [] } }. Finally, /mcp in Claude Code.

Q: What is plotly best for?

plotly is categorized under Data & Analytics. It covers: python, data-&-analytics, design.

New

19.9kSmitheryData & Analyticsby davila7

Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).

Summary

The plotly skill enables you to create interactive, publication-quality charts and visualizations directly from Claude Code using the Plotly Python library.

It supports a wide range of plot types from quick exploratory charts with Plotly Express to highly customized figures with graph objects, making it ideal for data analysis, reporting, and dashboard creation.

Install & Usage

Open your MCP config

~/.claude.json

Add the server config

Add the configuration to "mcpServers": { "plotly": { "command": "...", "args": [] } }

Restart Claude Code

/mcp

Use Cases

Generate an interactive scatter plot to explore correlations between two variables in a dataset.

Create a multi-trace line chart comparing time series trends across different categories.

Build a heatmap to visualize correlation matrix or geospatial data on a map.

Design a 3D surface plot to represent mathematical functions or spatial data.

Produce a statistical distribution plot (box plot, violin plot) to summarize data spread.

Export a plot as a static image (PNG, PDF) for inclusion in reports or presentations.

Usage Examples

/plotly Create an interactive scatter plot of the iris dataset with sepal length vs sepal width, colored by species.

/plotly Generate a line chart showing monthly sales for three product categories over the last two years.

/plotly Build a heatmap of the correlation matrix for the Boston housing dataset and save as a PNG image.

View source on GitHub

pythondata-&-analyticsdesign

Security Audits

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Frequently Asked Questions

What is plotly?

The plotly skill enables you to create interactive, publication-quality charts and visualizations directly from Claude Code using the Plotly Python library. It supports a wide range of plot types from quick exploratory charts with Plotly Express to highly customized figures with graph objects, making it ideal for data analysis, reporting, and dashboard creation.

How to install plotly?

To install plotly: open your mcp config (~/.claude.json), then add the config to "mcpServers": { "plotly": { "command": "...", "args": [] } }. Finally, /mcp in Claude Code.

What is plotly best for?

plotly is a mcp categorized under Data & Analytics. It is designed for: python, data-&-analytics, design. Created by davila7.

What can I use plotly for?

plotly is useful for: Generate an interactive scatter plot to explore correlations between two variables in a dataset.; Create a multi-trace line chart comparing time series trends across different categories.; Build a heatmap to visualize correlation matrix or geospatial data on a map.; Design a 3D surface plot to represent mathematical functions or spatial data.; Produce a statistical distribution plot (box plot, violin plot) to summarize data spread.; Export a plot as a static image (PNG, PDF) for inclusion in reports or presentations..