ParaView-MCP Server

Autonomous agent for scientific visualization using natural language

README.md

Paraview_MCP

ParaView-MCP is an autonomous agent that integrates multimodal large language models with ParaView through the Model Context Protocol, enabling users to create and manipulate scientific visualizations using natural language and visual inputs instead of complex commands or GUI operations. The system features visual feedback capabilities that allow it to observe the viewport and iteratively refine visualizations, making advanced visualization accessible to non-experts while augmenting expert workflows with intelligent automation.

Video Demo

Click the image below to watch the video:

Installation

git clone https://github.com/LLNL/paraview_mcp.git
cd paraview_mcp

conda create -n paraview_mcp python=3.10
conda install conda-forge::paraview
conda install mcp[cli] httpx

Setup for LLM

To set up integration with claude desktop, add the following to claude_desktop_config.json

    "mcpServers": {
      "ParaView": {
        "command": "/path/to/python",
        "args": [
        "/path/to/paraview_mcp/paraview_mcp_server.py"
        ]
      }
    }

running

1. Start paraview server

python pvserver --multi-clients

2. Connect to paraview server from paraview GUI (file -> connect)

3. Start claude desktop app


Citing Paraview_MCP

S. Liu, H. Miao, and P.-T. Bremer, “Paraview-MCP: Autonomous Visualization Agents with Direct Tool Use,” in Proc. IEEE VIS 2025 Short Papers, 2025, pp. 00

@inproceedings{liu2025paraview,
  title={Paraview-MCP: Autonomous Visualization Agents with Direct Tool Use},
  author={Liu, S. and Miao, H. and Bremer, P.-T.},
  booktitle={Proc. IEEE VIS 2025 Short Papers},
  pages={00},
  year={2025},
  organization={IEEE}
}

Authors

Paraview_MCP was created by Shusen Liu (liu42@llnl.gov) and Haichao Miao (miao1@llnl.gov)

License

Paraview_MCP is distributed under the terms of the BSD-3 license.

LLNL-CODE-2007260

Try it

Create a 3D surface plot of the loaded dataset.
Change the color map of the current visualization to cool-to-warm.
Add a slice filter to the dataset and display the result.
Adjust the camera angle to view the visualization from the top-down perspective.

Frequently Asked Questions

What are the key features of ParaView-MCP?

Autonomous creation and manipulation of scientific visualizations. Multimodal LLM integration for natural language control. Visual feedback capabilities for iterative refinement. Direct tool use for ParaView operations. Reduces reliance on complex GUI operations.

What can I use ParaView-MCP for?

Automating complex scientific visualization workflows for non-experts. Augmenting expert visualization tasks with intelligent automation. Iterative refinement of 3D scientific data representations. Replacing manual GUI interactions with natural language commands.

How do I install ParaView-MCP?

Install ParaView-MCP by running: git clone https://github.com/LLNL/paraview_mcp.git && cd paraview_mcp && conda create -n paraview_mcp python=3.10 && conda install conda-forge::paraview && conda install mcp[cli] httpx

What MCP clients work with ParaView-MCP?

ParaView-MCP works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep ParaView-MCP docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Open Conare