Blender MCP
Drive Blender from any AI assistant — objects, materials, rendering and Python scripting.
Last verified: August 26, 2026
How to Install Blender MCP
$pip install -e . (clone the repo, create a venv, then install the blender_mcp_bridge.zip add-on via Edit → Preferences → Add-ons → Install)Requires Claude Desktop, Cursor, Windsurf, or another MCP-compatible client.
About Blender MCP
Blender MCP lets an AI assistant control Blender through the Model Context Protocol. It exposes tools for creating objects, assigning materials, rendering images, exporting scenes, executing arbitrary Python inside Blender, and managing long-running async jobs. Implementations vary in scope, from around 27 tools across 7 namespaces up to community forks exposing roughly 270 direct-dispatch tools.
Blender MCP is a Design MCP server designed for developers and AI power users. It enables extending AI assistants with real-world capabilities by exposing a structured set of tools over the Model Context Protocol. Key capabilities include standards-based mcp server interface, works with claude, gpt, gemini, and other mcp clients, tool discovery and structured outputs, and structured tool calls that work cleanly inside an LLM context. It integrates with Claude Desktop, Cursor, Windsurf, and any MCP-compatible client, and is best suited for developers and AI power users who need ai engineers wiring assistants into real tools.
Key Features
- 3d
- design
- blender
- rendering
- creative
Pricing
- Core MCP server
- Community support
- Works with any MCP client
- Everything in Free
- Higher usage limits
- Priority support
- Everything in Pro
- SLA & SSO
- Dedicated support
Tier details are indicative — visit the Blender MCP website for current pricing.
Pros & Cons
Pros
- Drop-in support across MCP-compatible AI clients
- Reduces prompt boilerplate by exposing concrete tool calls
- Active community and ongoing updates
Cons
- Requires an MCP-capable client to use
- Initial setup can require configuration
- Capability surface depends on what the underlying service exposes
Best For
- AI engineers wiring assistants into real tools
- Teams adopting MCP as an integration standard
- Power users who want more than chat
Screenshots
Screenshots coming soon —
Submit yours →Our Take on Blender MCP
The most capable route into 3D work from an AI assistant, and the Python execution tool means you are never boxed in by the tool surface. Setup is the real cost — a venv plus a manual Blender add-on install is meaningfully more work than an npx one-liner.