Cloudcompare

Cross-platform Model Context Protocol (MCP) server for CloudCompare — lets AI assistants (Claude, etc.) process 3D point clouds and meshes via natural language.

Features

Native tools (no CloudCompare required)

Tool	Description
read_cloud_metadata	Parse a cloud and return point count, bounding box, extent, density, RGB/intensity/normals presence
visualize_cloud	Render top / front / side views + metadata panel as a base64 PNG the model can see directly

CloudCompare tools (requires CloudCompare installation)

Tool	Description
get_cloudcompare_info	Check installation & version
load_cloud_info	Inspect file stats via CloudCompare
subsample	Reduce density — random / spatial / octree
compute_cloud_to_cloud_distances	C2C nearest-neighbour distances
compute_cloud_to_mesh_distances	C2M signed distances
icp_registration	Align two clouds with ICP
compute_normals	Estimate surface normals
filter_by_scalar_field	Threshold points by scalar value
statistical_outlier_removal	Remove noise with SOR filter
merge_clouds	Merge multiple clouds into one
convert_format	Convert between LAS/LAZ, PLY, PCD, XYZ, E57, OBJ…
run_cloudcompare_command	Escape hatch for arbitrary CLI commands

How visualize_cloud works

visualize_cloud reads the point cloud natively in Python, renders a 4-panel figure, and returns an ImageContent (base64 PNG) alongside a JSON description. The model can see the image directly — no display or CloudCompare needed.

┌─────────────────┬─────────────────┐
│   Top  (XY)     │   Front  (XZ)   │
│                 │                 │
├─────────────────┼─────────────────┤
│   Side  (YZ)    │  Metadata stats │
│                 │  (pts, bbox,    │
│                 │   density, …)   │
└─────────────────┴─────────────────┘

Color modes: height (viridis Z gradient, default) · rgb (stored RGB) · intensity (plasma).

Requirements

• Python ≥ 3.10
• uv (recommended) or pip
• CloudCompare ≥ 2.12 — download (only for CloudCompare tools)

Python dependencies installed automatically: numpy, matplotlib, laspy[lazrs], plyfile.

Installation

Quickstart with uvx (no install needed)

uvx cloudcompare-mcp

Install locally

pip install cloudcompare-mcp
cloudcompare-mcp

CloudCompare binary detection

The server looks for CloudCompare in this order:

1. CLOUDCOMPARE_PATH environment variable
2. System PATH (cloudcompare / CloudCompare)
3. Platform default locations:

Platform	Default path
macOS	/Applications/CloudCompare.app/Contents/MacOS/CloudCompare
Windows	C:\Program Files\CloudCompare\cloudcompare.exe
Linux	/usr/bin/cloudcompare

Set CLOUDCOMPARE_PATH to override:

export CLOUDCOMPARE_PATH="/opt/custom/cloudcompare"

MCP client configuration

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "cloudcompare": {
      "command": "uvx",
      "args": ["cloudcompare-mcp"]
    }
  }
}

Claude Code (~/.claude/settings.json)

{
  "mcpServers": {
    "cloudcompare": {
      "command": "uvx",
      "args": ["cloudcompare-mcp"]
    }
  }
}

With a custom binary path:

{
  "mcpServers": {
    "cloudcompare": {
      "command": "uvx",
      "args": ["cloudcompare-mcp"],
      "env": {
        "CLOUDCOMPARE_PATH": "/path/to/cloudcompare"
      }
    }
  }
}

Usage example

Once configured in Claude Desktop or Claude Code:

"Load my scan.las file and subsample it spatially to 5 cm, then remove statistical outliers."

Claude will call the appropriate tools in sequence and report results.

Supported file formats

LAS · LAZ · PLY · PCD · XYZ · ASC · TXT · E57 · OBJ · BIN · SHP

License

MIT