Marmoset Toolbag 5 MCP Server
Enables AI assistants to control Marmoset Toolbag 5 for 3D rendering, lighting, scene management, and more via natural language.
README
🎨 Marmoset Toolbag 5 — MCP Server
Control Marmoset Toolbag 5 from any MCP-compatible AI client (Claude Desktop, Cursor, Windsurf, Agent Zero, etc.).
No more being the middle-man — your AI assistant talks directly to Marmoset.
Architecture
┌──────────────────┐ stdio ┌──────────────────┐ HTTP ┌──────────────────────┐
│ Claude Desktop │◄──────────────►│ MCP Server │◄──────────►│ MCP Bridge Plugin │
│ Cursor / etc. │ (MCP) │ server.py │ :8765 │ (inside Toolbag) │
│ │ │ (your machine) │ │ auto-loads on start │
└──────────────────┘ └──────────────────┘ └──────────────────────┘
Two components:
- MCP_Bridge.py — A Toolbag plugin that auto-loads when Marmoset starts. Exposes the
msetPython API over a local HTTP server with a status UI panel. - server.py — An MCP server that runs on your machine. Translates MCP tool calls into HTTP requests to the bridge plugin.
Quick Start
Step 1: Install the Marmoset Plugin
Copy bridge.py to your Marmoset Toolbag plugins folder and rename it:
Windows:
copy bridge.py "C:\Program Files\Marmoset Toolbag 5\data\plugins\MCP_Bridge.py"
macOS:
cp bridge.py "/Applications/Marmoset Toolbag 5.app/Contents/Resources/data/plugins/MCP_Bridge.py"
Restart Marmoset Toolbag. The plugin loads automatically and shows a status panel:
┌─ MCP Bridge ──────────────────┐
│ Status: ● Running │
│ Endpoint: http://127.0.0.1:8765 │
│ Actions: 23 │
│ Requests: 0 │
│ │
│ [ Stop Server ] │
└───────────────────────────────┘
You can toggle the server on/off with the button. No need to run scripts manually ever again.
Step 2: Set up the MCP Server (Miniconda)
Create a dedicated conda environment:
conda create -n marmoset-mcp python=3.11 -y
conda activate marmoset-mcp
pip install mcp[cli] httpx
Test that the server can start:
python server.py
Step 3: Connect your MCP client
Claude Desktop
Edit your claude_desktop_config.json:
Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"marmoset": {
"command": "C:/Users/YOU/miniconda3/envs/marmoset-mcp/python.exe",
"args": ["C:/path/to/server.py"]
}
}
}
Important: Use the full path to the conda environment's
python.exeso Claude Desktop picks up the right packages. Find it with:conda activate marmoset-mcp where python # Windows which python # macOS/Linux
Restart Claude Desktop. You'll see a 🔨 tool icon with Marmoset tools.
Cursor
Add to .cursor/mcp.json in your project or global Cursor settings:
{
"mcpServers": {
"marmoset": {
"command": "C:/Users/YOU/miniconda3/envs/marmoset-mcp/python.exe",
"args": ["C:/path/to/server.py"]
}
}
}
Custom Bridge URL
If the bridge runs on a different port or machine:
python server.py --bridge-url http://192.168.1.50:8765
Available MCP Tools (23 tools)
🔗 Connection
| Tool | Description |
|---|---|
ping |
Check if the Marmoset bridge is running |
🎬 Scene Management
| Tool | Description |
|---|---|
get_scene_info |
Object counts, types, scene bounds |
list_objects |
List all objects (optional type filter) |
import_model |
Import FBX, OBJ, etc. |
frame_scene |
Frame entire scene in camera |
frame_object |
Frame a specific object |
rename_object |
Rename any scene object |
remove_object |
Delete an object from the scene |
💡 Lighting
| Tool | Description |
|---|---|
list_lights |
List all lights with full properties |
add_light |
Create directional, spot, or omni lights |
modify_light |
Change any light property (color, temperature, position, shadows, gels, etc.) |
📷 Camera & Post-Processing
| Tool | Description |
|---|---|
set_camera |
Position, rotation, FOV, focal length |
set_post_effects |
Tone mapping, bloom, vignette, grain, contrast, clarity |
set_depth_of_field |
DOF focus distance, f-stop, bokeh |
set_lens |
Distortion, chromatic aberration, lens flares, motion blur |
🌅 Environment
| Tool | Description |
|---|---|
set_sky |
Sky brightness, rotation, procedural sky (time, latitude, turbidity, etc.) |
load_sky |
Load a .tbsky file |
import_sky_image |
Import HDR/EXR environment map |
set_fog |
Fog color, density, opacity |
🖼️ Rendering
| Tool | Description |
|---|---|
set_render_settings |
Ray tracing, shadows, AO, reflections, caustics |
render_image |
Render single image at specified resolution + samples |
render_images |
Render all cameras/passes |
⚡ Advanced
| Tool | Description |
|---|---|
execute_script |
Run arbitrary Python code inside Toolbag |
Built-in Prompts
The MCP server includes contextual prompt templates that guide the AI:
setup_cinematic_lighting— 3-point cinematic lighting rigsetup_studio_portrait— Portrait/character showcase lightingrender_for_portfolio— Portfolio-quality render workflow
Example Conversations
Once connected, just talk naturally:
You: "Set up cinematic lighting for my character"
AI: Inspects scene → creates key/fill/rim lights → configures post-effects
You: "Make it more dramatic with warmer tones"
AI: Adjusts light brightness ratios and color temperatures
You: "Render at 4K with ray tracing"
AI: Enables RT, sets quality, renders at 3840×2160
You: "Import my character from C:/exports/hero.fbx and set up a studio portrait"
AI: Imports model → frames it → builds portrait lighting rig
Workflow: iClone 8 / Character Creator → Marmoset
Export from iClone 8 / CC4
- Export as FBX (Binary, recommended)
- Enable Embed Textures or export textures to a subfolder
- Use iClone/CC default coordinate system
Import & Render in Marmoset (via AI)
- "Import C:/exports/my_character.fbx"
- "Set up studio portrait lighting"
- "Add some rim light from the left, increase bloom"
- "Render 4K PNG with transparency"
Plugin Configuration
Edit these constants at the top of bridge.py if needed:
| Setting | Default | Description |
|---|---|---|
BRIDGE_HOST |
"127.0.0.1" |
Bind address (use "0.0.0.0" for remote access) |
BRIDGE_PORT |
8765 |
HTTP port |
Troubleshooting
| Issue | Solution |
|---|---|
| "Cannot connect to bridge" | Check the MCP Bridge plugin panel in Marmoset — status should say "● Running" |
| Plugin doesn't appear | Verify the file is in the correct data/plugins/ folder and named .py |
| Bridge port conflict | Change BRIDGE_PORT in bridge.py and use --bridge-url for server.py |
| Light creation fails | Toolbag may need at least one light in the scene first — add one manually, then the AI can duplicate/modify it |
| Claude Desktop can't find packages | Use the full conda python path in the config, not just "python" |
| Slow responses | The plugin queues commands on Toolbag's main thread via onPeriodicUpdate. Close heavy scenes for faster response |
| Script errors | Check Toolbag's Python Console (Edit → Python Console) for error details |
Security Note
The bridge listens on 127.0.0.1 (localhost only) by default. To allow remote access, change BRIDGE_HOST in bridge.py to "0.0.0.0" — but only on trusted networks.
License
MIT — Free to use, modify, and distribute.
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