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Blender MCP: AI-Powered 3D Innovation & Lightning Efficiency - MCP Implementation

Blender MCP: AI-Powered 3D Innovation & Lightning Efficiency

Blender MCP harnesses Ollama’s lightning-fast LLMs for seamless AI-driven 3D creation – pro artists’ new essential toolkit for boundary-pushing creativity and razor-sharp efficiency.

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About Blender MCP

What is Blender MCP: AI-Powered 3D Innovation & Lightning Efficiency?

Blender MCP bridges the gap between human creativity and AI-driven 3D modeling through the Model Context Protocol (MCP). This open-source integration enables users to manipulate Blender’s powerful 3D environment using natural language prompts, powered by local AI models managed via Ollama. By decoupling interface complexity from AI logic, Blender MCP offers a seamless workflow for artists, designers, and developers to accelerate creation without sacrificing control.

Key Features of Blender MCP: AI-Powered 3D Innovation & Lightning Efficiency?

  • AI-Driven Workflow Automation: Execute actions like object creation, material assignment, and scene rendering via conversational commands.
  • Local Model Flexibility: Leverage Ollama’s ecosystem of models (e.g., Llama3, Gemma3) for tailored performance without cloud dependencies.
  • Asset Integration: Directly source textures and 3D models from PolyHaven using AI prompts, reducing manual asset hunting.
  • Programmatic Control: Access low-level Blender operations through structured tools like execute_blender_code for advanced users.

Blender MCP Features

How to Use Blender MCP: AI-Powered 3D Innovation & Lightning Efficiency?

Follow this streamlined workflow to harness the platform’s capabilities:

  1. Initialization: Start Ollama and the MCP server, then activate the Blender add-on from the sidebar.
  2. Command Execution: Use the mcp CLI tool to issue prompts like "Add a glowing sphere at (0,0,5)", letting the AI interpret intent and execute precise actions.
  3. Asset Management: Query PolyHaven categories via get_polyhaven_categories, then download assets like texture_id=PH_1234 for immediate application to objects.
  4. Advanced Control: Fine-tune outputs using parameters in structured tools, such as specifying resolution=4K for renders or material_name=metallic for textures.

Use Cases of Blender MCP: AI-Powered 3D Innovation & Lightning Efficiency?

  • Rapid Prototyping: Ideate and iterate designs at speed by verbally describing concepts like "Create a low-poly forest with 20 trees."
  • Asset Enrichment: Automatically fetch and apply high-quality HDRIs or PBR textures from PolyHaven to elevate scene realism.
  • Collaborative Workflows: Document and reproduce workflows using CLI commands, enabling team members to replicate setups through shared prompt scripts.
  • Accessibility Enhancement: Democratize Blender’s complexity by letting non-technical users interact with the tool through conversational inputs.

Blender MCP FAQ

FAQ from Blender MCP: AI-Powered 3D Innovation & Lightning Efficiency?

Q: Why does the server require Ollama?
Ollama’s local model hosting ensures fast inference times and privacy, avoiding latency from cloud APIs while supporting large models.

Q: How do I switch AI models?
Use set_ollama_model "gemma3" in your prompt or adjust server settings during startup for immediate context switching.

Q: Can I extend the toolset?
Yes! The MCP framework allows developers to register custom tools in src/blender_open_mcp/tools.py, enabling domain-specific extensions like character rigging or animation controls.

Q: What if the AI misinterprets my prompt?
Refine instructions incrementally. For example, after "Create a cube" yields a default object, follow up with "Resize the cube to 2x scale" for precise adjustments.

Content

blender-open-mcp

blender-open-mcp is an open source project that integrates Blender with local AI models (via Ollama) using the Model Context Protocol (MCP). This allows you to control Blender using natural language prompts, leveraging the power of AI to assist with 3D modeling tasks.

Features

  • Control Blender with Natural Language: Send prompts to a locally running Ollama model to perform actions in Blender.
  • MCP Integration: Uses the Model Context Protocol for structured communication between the AI model and Blender.
  • Ollama Support: Designed to work with Ollama for easy local model management.
  • Blender Add-on: Includes a Blender add-on to provide a user interface and handle communication with the server.
  • PolyHaven Integration (Optional): Download and use assets (HDRIs, textures, models) from PolyHaven directly within Blender via AI prompts.
  • Basic 3D Operations:
    • Get Scene and Object Info
    • Create Primitives
    • Modify and delete objects
    • Apply materials
  • Render Support: Render images using the tool and retrieve information based on the output.

Installation

Prerequisites

  1. Blender: Blender 3.0 or later. Download from blender.org.
  2. Ollama: Install from ollama.com, following OS-specific instructions.
  3. Python: Python 3.10 or later.
  4. uv: Install using pip install uv.
  5. Git: Required for cloning the repository.

Installation Steps

  1. Clone the Repository:

    git clone https://github.com/dhakalnirajan/blender-open-mcp.git

cd blender-open-mcp
  1. Create and Activate a Virtual Environment (Recommended):

    uv venv

source .venv/bin/activate  # On Linux/macOS
.venv\Scripts\activate  # On Windows
  1. Install Dependencies:

    uv pip install -e .

  2. Install the Blender Add-on:

* Open Blender.
* Go to `Edit -> Preferences -> Add-ons`.
* Click `Install...`.
* Select the `addon.py` file from the `blender-open-mcp` directory.
* Enable the "Blender MCP" add-on.
  1. Download an Ollama Model (if not already installed):

    ollama run llama3.2

(Other models like Gemma3 can also be used.)

Setup

  1. Start the Ollama Server: Ensure Ollama is running in the background.

  2. Start the MCP Server:

    blender-mcp

Or,

    python src/blender_open_mcp/server.py

By default, it listens on http://0.0.0.0:8000, but you can modify settings:

    blender-mcp --host 127.0.0.1 --port 8001 --ollama-url http://localhost:11434 --ollama-model llama3.2
  1. Start the Blender Add-on Server:
* Open Blender and the 3D Viewport.
* Press `N` to open the sidebar.
* Find the "Blender MCP" panel.
* Click "Start MCP Server".

Usage

Interact with blender-open-mcp using the mcp command-line tool:

Example Commands

  • Basic Prompt:

    mcp prompt "Hello BlenderMCP!" --host http://localhost:8000
    
  • Get Scene Information:

    mcp tool get_scene_info --host http://localhost:8000
    
  • Create a Cube:

    mcp prompt "Create a cube named 'my_cube'." --host http://localhost:8000
    
  • Render an Image:

    mcp prompt "Render the image." --host http://localhost:8000
    
  • Using PolyHaven (if enabled):

    mcp prompt "Download a texture from PolyHaven." --host http://localhost:8000
    

Available Tools

Tool Name Description Parameters
get_scene_info Retrieves scene details. None
get_object_info Retrieves information about an object. object_name (str)
create_object Creates a 3D object. type, name, location, rotation, scale
modify_object Modifies an object’s properties. name, location, rotation, scale, visible
delete_object Deletes an object. name (str)
set_material Assigns a material to an object. object_name, material_name, color
render_image Renders an image. file_path (str)
execute_blender_code Executes Python code in Blender. code (str)
get_polyhaven_categories Lists PolyHaven asset categories. asset_type (str)
search_polyhaven_assets Searches PolyHaven assets. asset_type, categories
download_polyhaven_asset Downloads a PolyHaven asset. asset_id, asset_type, resolution, file_format
set_texture Applies a downloaded texture. object_name, texture_id
set_ollama_model Sets the Ollama model. model_name (str)
set_ollama_url Sets the Ollama server URL. url (str)
get_ollama_models Lists available Ollama models. None

Troubleshooting

If you encounter issues:

  • Ensure Ollama and the blender-open-mcp server are running.
  • Check Blender’s add-on settings.
  • Verify command-line arguments.
  • Refer to logs for error details.

For further assistance, visit the GitHub Issues page.


Happy Blending with AI! 🚀

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