About PyVista MCP Server
PyVista MCP Server wraps PyVista 3D visualization in an MCP tool. Its hello_world tool creates a grid of 3D shapes and exports an interactive HTML file for viewing in a browser.
Key features
- 01Generate a 3×3 grid of 3D shapes
- 02Include shapes such as cylinders, arrows, and spheres
- 03Export an interactive HTML file
Use cases
- 01Create a sample of 3D shapes
- 02View interactive visualizations in a browser
- 03Invoke the PyVista demo tool through MCP
MCP support
The MCP server exposes a hello_world tool to MCP clients for generating and exporting a 3D visualization as an HTML file.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEPyVista MCP Server
This repository contains a PyVista-based MCP (Model Context Protocol) server. It demonstrates the integration of PyVista for 3D visualization with MCP tools.
Features
- hello_world Tool: A tool that generates and exports a 3x3 grid of 3D shapes (Cylinder, Arrow, Sphere, etc.) as an interactive HTML file.
Output
The hello_world tool exports an HTML file named a_basic.html in the current working directory. Open this file in a web browser to view the interactive 3D visualization.
Configuration
To configure the MCP server, use the following JSON structure in your settings:
{
"mcpServers": {
"mcp-demo-server": {
"disabled": false,
"timeout": 600,
"command": "<path-to-python-executable>",
"args": ["<path-to-server-script>"],
"transportType": "stdio"
}
}
}
This configuration specifies the command and arguments to run the MCP server, along with other settings like timeout and transport type.
Example Usage
https://github.com/user-attachments/assets/244d7f7d-1432-4d11-8b12-b0138e97746a
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.