holoviz-mcp-cli
holoviz-mcp CLI
The holoviz-mcp CLI provides direct access to HoloViz documentation, component introspection, and visualization tools from the command line.
Installation
The recommended way to install is as a uv tool:
uv tool install holoviz-mcp
This installs both holoviz-mcp and hv commands into an isolated environment. Use hv as a shorter alternative in all examples below (e.g., hv search Panel Tabulator, hv pn get Button).
When to Use CLI vs MCP
- Prefer MCP tools when the HoloViz MCP server is loaded — they return structured, typed data (including images) and integrate natively with LLM tool calling
- Use CLI when MCP tools are not available but
holoviz-mcp(orhv) is installed and you have Bash/shell access - Search the web as a last resort when neither MCP tools nor CLI are available
Output Formats
More from marcskovmadsen/holoviz-mcp
panel
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.
13panel-material-ui
Best practices for developing modern looking tools, dashboards and data apps using HoloViz Panel and Panel Material UI components.
10hvplot
Best practices for doing quick exploratory data analysis with minimal code and a Pandas .plot like API using HoloViews hvPlot.
7param
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.
6panel-holoviews
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.
6holoviews
Best practices for developing advanced, interactive, and publication-quality data visualizations using HoloViz HoloViews
6