holoviz-mcp

Best practices for developing advanced, interactive, and publication-quality data visualizations using HoloViz HoloViews

Command reference for the holoviz-mcp CLI tool. Use the CLI when you have Bash/shell access and want direct access to HoloViz documentation, component introspection, and visualization tools.

Best practices for doing quick exploratory data analysis with minimal code and a Pandas .plot like API using HoloViews hvPlot.

Build custom Panel components using JSComponent (vanilla JS, web components), ReactComponent (React/JSX), AnyWidgetComponent (AnyWidget spec for cross-platform), or MaterialUIComponent (Material UI themed). Use when wrapping JS libraries, creating interactive widgets, or building themed components. Includes decision guide, best practices, DOs/DON'Ts, and Playwright UI testing patterns.

Best practices for integrating HoloViews and hvPlot visualizations into Panel applications. Use when embedding HoloViews/hvPlot plots in Panel panes, preserving zoom/pan state across data refreshes with DynamicMap, composing DynamicMap overlays without type errors, using HoloViews streams (Selection1D, RangeXY, Tap, BoundsXY, Pipe, Buffer) with Panel, cross-filtering with link_selections, making HoloViews plots responsive in Panel layouts, or wiring Panel widgets to Bokeh plot properties with jslink.

Best practices for developing modern looking tools, dashboards and data apps using HoloViz Panel and Panel Material UI components.

Best practices for developing tools, dashboards and interactive data apps with HoloViz Panel. Create reactive, component-based UIs with widgets, layouts, templates, and real-time updates. Use when developing interactive data exploration tools, dashboards, data apps, or any interactive Python web application. Supports file uploads, streaming data, multi-page apps, and integration with HoloViews, hvPlot, Pandas, Polars, DuckDB and the rest of the HoloViz and PyData ecosystems.

Use when building Python classes with validated, typed parameters using the Param library. Triggers include creating configuration classes, building reusable components with state, implementing reactive dependencies between parameters, adding type-safe attributes with bounds/constraints, creating testable parameterized classes, or when users mention param.Parameterized, @param.depends, or param.watch.