Marmoset Toolbag 5 MCP Server

Marmoset Toolbag 5 MCP Server

Enables AI assistants to control Marmoset Toolbag 5 for 3D rendering, lighting, scene management, and more via natural language.

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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:

  1. MCP_Bridge.py — A Toolbag plugin that auto-loads when Marmoset starts. Exposes the mset Python API over a local HTTP server with a status UI panel.
  2. 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.exe so 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 rig
  • setup_studio_portrait — Portrait/character showcase lighting
  • render_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

  1. Export as FBX (Binary, recommended)
  2. Enable Embed Textures or export textures to a subfolder
  3. Use iClone/CC default coordinate system

Import & Render in Marmoset (via AI)

  1. "Import C:/exports/my_character.fbx"
  2. "Set up studio portrait lighting"
  3. "Add some rim light from the left, increase bloom"
  4. "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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