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3D Visualizer

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
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Inspect, compare and export point clouds, meshes and calibrated depth data with inline 3D previews.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for 3D Visualizer, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

3D Visualizer

View, compare and inspect point clouds, meshes, gaussian splats, depth maps and disparity images in your editor or browser β€” with Rust and WebAssembly doing the heavy decoding, so files with millions of points open in seconds.

Depth image converted to a point cloud

Highlights

  • Open large point clouds quickly, including files with millions of points
  • Decode the demanding formats in Rust/WebAssembly β€” LAS, LAZ, E57 and TIFF β€” alongside Rust geometry kernels for camera models and scan registration
  • Compare multiple point clouds in one view and toggle them independently
  • Convert depth and disparity images into point clouds
  • Render gaussian splat reconstructions as sorted splats or center point clouds
  • Inspect meshes as surfaces, wireframes, points and normals
  • Use Eye-Dome Lighting and brightness correction for clearer uncolored geometry
  • Measure distances and adjust camera, rotation center and view parameters
  • Use the shared viewer on the website
  • Try the local Python package and command-line viewer for 3D files, NumPy/PyTorch arrays and inline local notebooks (uv add 3d-visualizer)
  • Connect AI agents through the local MCP server to open scenes, control the camera and inspect rendered screenshots

Supported formats

TypeFormats
Point cloudsPLY, XYZ, XYZN, XYZRGB, PCD, PTS, NPY, LAS, LAZ, E57, KITTI BIN, Stonex X3A/X3R (experimental)
MeshesPLY, OBJ, STL, OFF, GLTF, GLB, FBX, DAE (Collada), 3DS
Gaussian splats3DGS PLY, SPZ, SPLAT, KSPLAT, SOG
Depth/disparity imagesTIFF, PNG, PFM, NPY, NPZ
3D Body PosesJSON pose data (experimental)
Camera ProfilesJSON pose data (experimental)

Model animation playback and remote URL loading are supported; see model details and remote files.

Because .bin and .json are generic extensions, neither is opened with the 3D Visualizer by default. For KITTI BIN, use Open With... or right-click and choose Open with 3D Visualizer. For a supported JSON pose, right-click and choose Load JSON as 3D Pose.

Features

Depth and Disparity to Point Cloud

Convert depth or disparity images into point clouds. Projection settings include fx, fy, cx, cy, camera distortion models, mono depth scale and bias, PNG int16 scale and disparity offset.

Eye-Dome Lighting

Use Eye-Dome Lighting to improve depth perception, especially for uncolored point clouds.

Eye-Dome Lighting

Multiple Point Clouds

Load multiple point clouds into the same view, toggle them independently and switch between them with Shift-click.

Multiple point clouds

Mesh Inspection

Inspect mesh files with controls for surface, wireframe, points and normals. This is useful when checking geometry, topology or exported reconstruction results without leaving the editor.

Gaussian Splatting

Open 3D Gaussian Splatting reconstructions (3DGS PLY, SPZ, SPLAT, KSPLAT, SOG) and render them as real sorted splats via Spark, or as a point cloud of the gaussian centers with colors derived from the spherical-harmonics coefficients. Switch per file with the ✨ Splats button in the Files panel. Measurement and picking keep working on the gaussian centers in splat mode. Oversized background gaussians can be reduced with the logarithmic Max splat size control, while coloring center points by the opacity scalar field in Points mode helps with spotting floaters.

Point Cloud Attributes

Point cloud files can include positions, RGB colors, normals and scalar fields. The viewer uses positions for geometry, original RGB values when available, normals for inspection, and intensity/reflectivity fields for optional scalar coloring. The recognized property names are x/y/z, red/green/blue, nx/ny/nz and intensity/reflectivity/reflectance/remission. Any other numeric per-vertex PLY property (e.g. confidence, error, curvature) also appears in the Color dropdown for Viridis or grayscale colormap coloring. LAS/LAZ attributes such as classification, returns, scan angle and GPS time are exposed through the same scalar-field color controls. E57 containers load each scan as a separate, independently visible entry.

Distance Measurement Tools and Camera Manipulation

Build multiple measurement paths with Shift-double-click. See control settings for options.

Camera Recording

Create smooth camera paths from keyframes and export them as configurable video recordings.

Navigation

Double-click a point to change the rotation center. This allows for easy navigation using a mouse or a trackpad. You can also manually enter the camera position, rotation center and viewing angle.

Performance-Aware Rendering

The viewer shows the current frame rate. When the point cloud is not moving, no more frames are generated, which helps reduce power usage.

NPY file structure options

  • As a depth image: [X,Y]
  • As a point cloud: [...,3] with the three values X,Y,Z

Feature requests and issues

If you have a workflow that would benefit from new features or file formats, please open an issue on the GitHub repository. Example files are especially helpful when adding support for new formats.

Roadmap

  • Add support for more file formats
  • Improve dataset support with example images from Middlebury stereo and ETH3D
  • Use calibration files next to depth images automatically when available (example files needed)
  • Accept 3d body pose files (example files needed)

Links

  • VS Code Marketplace: Install extension
  • Open VSX: Install extension
  • JetBrains: Signed preview and installation
  • Website: 3d.f-kleinicke.de
  • Documentation: User guides and MCP reference
  • Standalone app: Tauri desktop preview
  • PyPI (Python and CLI): 3d-visualizer
  • MCP: Supported β€” Agent setup and usage
  • More platforms: Coming soon
  • Blog: Coming soon
  • Videos: Coming soon

Listed on mcpservers.org

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about 3D Visualizer

We don't have a confirmed install command for 3D Visualizer yet, so we don't publish a generated one β€” a guessed package name would point at the wrong package or none at all. Follow the project's own README or setup instructions (https://github.com/kleinicke/ply-visualizer) for the current steps.

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
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Last updatedSep 28, 2026
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Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools12/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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