kimimgo/viznoir
๐ ๐ ๐ง - Cinema-quality science visualization MCP server for CFD/FEA/SPH. 22 tools for rendering, slicing, contouring, volume rendering, and animating OpenFOAM/VTK/CGNS data. Headless EGL/OSMesa.
Quick Install
{
"mcpServers": {
"kimimgo-viznoir": {
"command": "npx",
"args": [
"-y",
"kimimgo-viznoir"
]
}
}
}Using an AI coding agent (Claude Code, Cursor, etc.)? Copy a ready-made prompt that tells it to fetch the setup instructions and install this server for you.
Documentation Overview
viznoir
VTK is all you need. Cinema-quality science visualization for AI agents.

One prompt โ physics analysis โ cinematic renders โ LaTeX equations โ publication-ready story.
What it does
An MCP server that gives AI agents full access to VTK's rendering pipeline โ no ParaView GUI, no Jupyter notebooks, no display server. Your agent reads simulation data, applies filters, renders cinema-quality images, and exports animations, all headless.
Works with: Claude Code ยท Cursor ยท Windsurf ยท Gemini CLI ยท any MCP client
Quick Start
1. Install
pip install viznoir
# With optional extras
pip install "viznoir[mesh]" # meshio + trimesh (50+ formats)
pip install "viznoir[composite]" # Pillow + matplotlib (split_animate)
pip install "viznoir[all]" # everything
Requires Python โฅ3.10. VTK wheel auto-installed (EGL headless rendering supported).
2. Verify
mcp-server-viznoir --help # server entry point
python -c "import viznoir; print(viznoir.__version__)"
3. Use with an MCP client
Add to your MCP client config (claude_desktop_config.json, ~/.cursor/mcp.json, etc.):
{
"mcpServers": {
"viznoir": {
"command": "mcp-server-viznoir",
"env": {
"VIZNOIR_DATA_DIR": "/path/to/your/simulation/data",
"VIZNOIR_OUTPUT_DIR": "/path/to/output"
}
}
}
}
Then ask your AI agent:
"Open cavity.foam, render the pressure field with cinematic lighting, then create a physics decomposition story."
4. Or use as a Python library (advanced)
All tool implementations are importable as async functions. You provide a VTKRunner and await the result:
import asyncio
from viznoir.core.runner import VTKRunner
from viznoir.tools.inspect import inspect_data_impl
from viznoir.tools.render import render_impl
async def main():
runner = VTKRunner()
meta = await inspect_data_impl(file_path="cavity.foam", runner=runner)
print(meta["fields"], meta["timesteps"])
result = await render_impl(
file_path="cavity.foam",
field_name="p",
runner=runner,
colormap="Cool to Warm",
camera="isometric",
width=1920, height=1080,
output_filename="pressure.png",
)
print(result.file_path)
asyncio.run(main())
See docs for the full tool reference.
Capabilities
| Category | Tools |
|---|---|
| Rendering | render ยท cinematic_render ยท batch_render ยท volume_render |
| Filters | slice ยท contour ยท clip ยท streamlines ยท pv_isosurface |
| Analysis | inspect_data ยท inspect_physics ยท extract_stats ยท analyze_data |
| Probing | plot_over_line ยท integrate_surface ยท probe_timeseries |
| Animation | animate ยท split_animate |
| Comparison | compare ยท compose_assets |
| Export | preview_3d ยท execute_pipeline |
22 tools ยท 12 resources ยท 4 prompts ยท 50+ file formats (OpenFOAM, VTK, CGNS, Exodus, STL, glTF, โฆ)
Showcase โ 10 Domains, One Pipeline
Every frame below is a single MCP tool call. No GUI, no post-processing, no ParaView. Annotations are rendered inside the 3D scene via VTK-native text actors and leader lines โ no Photoshop, no matplotlib overlay.
![]() | ![]() | ![]() | ![]() | ![]() |
| Medical CT skull volume | CFD Combustion streamlines | Thermal Heatsink gradient | Geoscience Seismic wavefield | Automotive DrivAerML ยท 8.8M cells |
![]() | ![]() | ![]() | ![]() | ![]() |
| Molecular HโO electron density | Vascular Cerebral aneurysm MRA | Planetary Bennu ยท 196K triangles | Structural Cantilever FEA stress | Volume Thermal threshold |
Physics-Aware Animations
Seven presets convert raw simulation data into publication-ready motion โ each binds a rendering primitive to a physical phenomenon.
| Preset | Physics | Rendering |
|---|---|---|
streamline_growth | Lagrangian advection | Particle path-line extension over time |
clip_sweep | Pressure gradient cross-section | Moving clip plane |
layer_reveal | CT density classification | Progressive isosurface stacking |
iso_sweep | Orbital topology | Isovalue sweep with camera orbit |
warp_oscillation | Structural mode shape | Warp-by-vector harmonic displacement |
light_orbit | Oblique illumination | Rotating key light for material reveal |
threshold_reveal | Feature hierarchy | Threshold peeling from outside โ in |
Story Composition (compose_assets)

Inspect โ render โ annotate โ compose โ narrate. One prompt produces a 4-panel physics decomposition with LaTeX-rendered governing equations.
Layouts: story (vertical narrative) ยท grid (NรM comparison) ยท slides (16:9 keynote) ยท video (MP4 with transitions)
Full interactive gallery: https://kimimgo.github.io/viznoir/#showcase
Architecture
prompt "Render pressure from cavity.foam"
โ
MCP Server 22 tools ยท 12 resources ยท 4 prompts
โ
VTK Engine readers โ filters โ renderer โ camera
โ EGL/OSMesa headless ยท cinematic lighting
Physics Layer topology analysis ยท context parsing
โ vortex detection ยท stagnation points
Animation 7 physics presets ยท easing ยท timeline
โ transitions ยท compositor ยท video export
Output PNG ยท WebP ยท MP4 ยท GLTF ยท LaTeX
Numbers
| 22 MCP tools | 24 VTK filters |
| 10 domains | 19 native file formats |
| 6/6 VTK data types | 50+ formats via meshio |
Documentation
Homepage: kimimgo.github.io/viznoir
Developer docs: kimimgo.github.io/viznoir/docs โ full tool reference, domain gallery, architecture guide
License
MIT









