Skip to main content

Nova3D MCP server — structured, part-aware 3D generation for AI agents

Project description

nova3d-mcp

Structured, part-aware 3D generation for AI agents.

nova3d-mcp is an MCP server that exposes Nova3D's generation pipeline as a callable tool inside Claude Code, Cursor, and any MCP-compatible agent.

One tool call. A washing machine comes back with named drum, door, control panel, and hose connectors — separately editable, not fused into a blob.


Why Nova3D

Every major AI 3D generator today produces mesh blobs — a single fused object that looks plausible in a render and collapses the moment you try to edit, rig, or pipeline it.

Nova3D is different. Instead of diffusion → mesh, it runs:

prompt / image
      ↓
LLM writes Blender Python construction code
      ↓
headless Blender executes + validates + repairs
      ↓
structured GLB — named parts, intact hierarchy, real joints

The result is a 3D asset that survives contact with real workflows: game engines, configurators, robotics simulations, AR scenes. Parts have names. Hierarchy is intact. Joints are real. You can change one component without regenerating everything.


Quickstart

1. Install

Once on PyPI (coming soon):

uvx nova3d-mcp

From source (available now):

git clone https://github.com/RareSense/nova3d-mcp.git
cd nova3d-mcp
python3.10 -m venv .venv && source .venv/bin/activate
pip install .

2. Get an API key

Sign in at nova3d.xyz, go to Settings → API Keys, and create a key.

export NOVA3D_TOKEN="n3d_your-api-key-here"

API keys never expire unless revoked. The MCP server validates your key on startup and prints a clear error if it's missing or invalid.

3. Add to Claude Code

Once on PyPI:

{
  "mcpServers": {
    "nova3d": {
      "command": "uvx",
      "args": ["nova3d-mcp"],
      "env": {
        "NOVA3D_TOKEN": "n3d_your-api-key-here"
      }
    }
  }
}

From source (after pip install .):

{
  "mcpServers": {
    "nova3d": {
      "command": "nova3d-mcp",
      "env": {
        "NOVA3D_TOKEN": "n3d_your-api-key-here"
      }
    }
  }
}

4. Generate

Generate a vending machine with separate door, glass panel, coin slot,
button grid, frame, and interior shelving. Use Google Gemini with my
API key AIza...

The agent calls generate_3d. You get back:

{
  "glb_url": "https://nova3d.xyz/assets/abc123.glb",
  "preview_url": "https://nova3d.xyz/preview/state-...",
  "parts": ["door", "glass_panel", "coin_slot", "button_grid", "frame", "shelf_1", "shelf_2"],
  "joint_count": 1,
  "code_artifact": { ... },
  "workflow_id": "state-..."
}

Open preview_url in your browser — interactive Three.js viewer, named parts, orbit controls, part explosion. No Blender required to preview.


Tools

generate_3d

Generate a structured 3D asset from text (and optional reference image).

Parameter Type Required Description
prompt string Asset description. Be specific about parts.
provider string "google" · "anthropic" · "openai"
api_key string Your BYOK key for the provider
llm string Model ID. Defaults to recommended per provider.
image_base64 string Reference image as plain base64
image_mime string e.g. "image/jpeg"

Recommended provider: google with gemini-2.0-flash — best spatial reasoning for complex multi-part objects.


regenerate_part

Regenerate one named part without rebuilding the whole asset.

Parameter Type Required Description
code_artifact object From prior generate_3d result
part_type string Part name e.g. "door", "handle"
description string What the new part should look like
provider string LLM provider
api_key string BYOK key
llm string Model ID

Finding part names: Open the preview_url from your generation — each mesh is labeled. Use that exact name as part_type.


add_part

Add a new component to an existing asset.

Parameter Type Required Description
code_artifact object From prior generation result
description string Description of the new part and where it goes
provider string LLM provider
api_key string BYOK key
llm string Model ID

articulate_model

Add joints, hinges, or rotational articulation to an existing asset.

Parameter Type Required Description
code_artifact object From prior generation result
model_url string glb_url from prior generation
articulation_request string What should move and how
provider string LLM provider
api_key string BYOK key
llm string Model ID
selected_meshes list Specific mesh names to articulate

get_generation_status

Check the status of a running workflow by ID.

Parameter Type Required Description
workflow_id string From any prior generation tool

Typical workflow

1. generate_3d("robot dog with four legs, head, torso, and tail")
   → glb_url, preview_url, parts, code_artifact

2. Open preview_url in browser
   → see named parts, identify what needs changing

3. regenerate_part(code_artifact, part_type="head", description="...")
   → updated glb_url, new preview_url

4. articulate_model(code_artifact, model_url, "make legs rotate at hip joints")
   → glb_url with working joints

Provider reference

Provider provider Default llm Notes
Google Gemini google gemini-2.0-flash Recommended
Anthropic anthropic claude-sonnet-4-20250514 Strong reasoning
OpenAI openai gpt-4o Widely available

Environment variables

Variable Required Description
NOVA3D_TOKEN API key from nova3d.xyz → Settings → API Keys (recommended) or session JWT
NOVA3D_API_URL Override API base URL (default: https://nova3d.xyz/api)

How it differs from blender-mcp

blender-mcp (21.9k ★) gives AI agents a remote control for a locally running Blender instance. It requires Blender installed, produces unstructured output, and inherits all the bpy hallucination problems of raw LLM → Blender code generation.

nova3d-mcp is different in kind:

blender-mcp nova3d-mcp
Blender required Yes No
Output Unstructured scene Named, hierarchical GLB
Validation None Server-side repair loop
Part awareness No Yes — named, addressable
Joints Manual scripting First-class output
Hosted backend No Yes

Contributing

Issues, PRs, and workflow feedback welcome. github.com/RareSense/nova3d-mcp

Community Discord: discord.gg/QEH8mzcwdR


License

MIT — see LICENSE

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nova3d_mcp-0.1.0.tar.gz (30.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

nova3d_mcp-0.1.0-py3-none-any.whl (16.9 kB view details)

Uploaded Python 3

File details

Details for the file nova3d_mcp-0.1.0.tar.gz.

File metadata

  • Download URL: nova3d_mcp-0.1.0.tar.gz
  • Upload date:
  • Size: 30.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.12

File hashes

Hashes for nova3d_mcp-0.1.0.tar.gz
Algorithm Hash digest
SHA256 2022eb33475503cebd435816b4ae66150c1a180604a2827ba40a3d2647b0434e
MD5 fae00bc90baab41b2c2bebd0f08d0fca
BLAKE2b-256 36a45a0205eaf97fbaf2bb2a989ccf88c8c61efbf879292bd8d5c748ebe00880

See more details on using hashes here.

File details

Details for the file nova3d_mcp-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: nova3d_mcp-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 16.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.12

File hashes

Hashes for nova3d_mcp-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 cc54bcc23d2db662b1922bdc78b2c959ef3c8f35485f34ff62a9c4d5f5720bba
MD5 012520e0683392396794479190d0f0b5
BLAKE2b-256 87219be7ff4420e5bb6e5b5846f378ef84f79b09e39bdbe22894a2ce816f51c6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page