Blender MCP

Overview

Blender MCP (also known as BlenderMCP) by Siddharth Ahuja is the leading open-source Model Context Protocol (MCP) server that bridges AI language models — especially Claude — with Blender, the powerful free and open-source 3D creation suite.

It allows AI assistants to directly interact with a live Blender session: creating objects, modifying geometry, applying materials, setting up lighting, rendering scenes, and more — all through natural language prompts.

The system uses a dual architecture: a Blender addon that exposes a socket server inside Blender, and a Python MCP server that translates AI tool calls into Blender Python API (bpy) commands.

Key Features

• Natural Language 3D Control: Prompt Claude to "create a low-poly mountain with snow caps" or "add a realistic car model and animate the wheels".
• Real-time Scene Manipulation: Add, edit, delete objects; modify meshes, apply modifiers, set materials, cameras, and lights.
• Inspection & Analysis: Query current scene state, list objects, analyze geometry, or get render previews.
• Automation Workflows: Generate complex scenes, iterate on designs, export models, or run batch operations.
• Live Connection: Works with a running Blender instance for immediate visual feedback.
• MCP Client Support: Compatible with Claude Desktop, Cursor, VS Code with MCP extensions, and other compliant AI tools.
• Extensible: Community forks add more tools, support for other LLMs (Ollama, Gemini), or specialized features like text-to-4D.

Use Cases

• AI-Assisted 3D Modeling: Generate 3D assets, characters, environments, or product visualizations from text descriptions.
• Rapid Prototyping: Iterate on designs conversationally without deep Blender knowledge.
• Scene Building & Storytelling: Create animated scenes, architectural visualizations, or game assets.
• Education & Learning: New users learn Blender while the AI handles complex operations.
• Creative Pipelines: Combine with other MCP servers (e.g., image generation or code tools) for full AI-driven content creation.
• Automation & Batch Processing: Script repetitive modeling tasks via AI orchestration.

Installation & Setup

1. Blender Addon

• Download addon.py from the repository.
• In Blender: Edit → Preferences → Add-ons → Install → Enable "Blender MCP".
• Open the sidebar (N key) → Blender MCP tab → Start the internal socket server.

2. MCP Server

• Install via pip install blender-mcp or clone the repo.
• Run the server (default port 9876).

3. Connect to AI Client

• Add the MCP server to Claude Desktop, Cursor, or your preferred client configuration.
• Start prompting in natural language while Blender is open.

Many YouTube tutorials provide step-by-step visual guides for Windows, macOS, and Linux.

Alternatives & Community

Several forks and variants exist, including:

• PolyMCP / llm-use Blender-MCP-Server (50+ tools, HTTP-based).
• Open-source LLM variants (Ollama integration).
• Enhanced versions for specific workflows (e.g., text-to-4D, VXAI).

The original ahujasid/blender-mcp remains the most popular and widely referenced implementation (thousands of stars and active community usage).

Compatibility

• Blender: Works with recent versions supporting Python scripting.
• Clients: Claude Desktop, Cursor, any MCP-compliant AI application.
• License: Open-source (MIT-style, check repo for details).

Blender MCP represents a major leap toward AI-native 3D content creation, dramatically lowering the barrier for generating high-quality 3D models and scenes.