Immunogenic-prismspectroscope589/Blender_mcp
Control and automate Blender 3D scenes using AI agents via MCP with scalable toolsets, multilingual support, and robust execution.
Platform-specific configuration:
{
"mcpServers": {
"Blender_mcp": {
"command": "npx",
"args": [
"-y",
"Blender_mcp"
]
}
}
}Add the config above to .claude/settings.json under the mcpServers key.
> Inspired by [blender-mcp](https://github.com/ahujasid/blender-mcp) by Siddharth Ahuja — the original proof-of-concept that demonstrated connecting AI agents to Blender over MCP. This project builds on that idea with a production-grade architecture: 69 tool groups, 550+ actions, multilingual intent routing, BVH assembly analysis, thread-safe execution, and a 499-test suite.
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Control Blender with AI — naturally, reliably, at production scale.
Give Claude, GPT, or any MCP-capable AI the ability to create, inspect, and animate 3D scenes in Blender using plain language and structured tool calls.
[](https://www.python.org/) [](https://www.blender.org/) [](https://modelcontextprotocol.io/) [](LICENSE)
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MCP (Model Context Protocol) is an open standard that lets AI assistants call structured tools — the same way a programmer calls an API. This project implements an MCP server that bridges your AI assistant to a live Blender session running on your computer.
In practice: tell your AI *"create a red metallic sphere above the cube"* or *"check if all drone parts are touching"* and it will call the right Blender tools, get real geometry data back, and show you a screenshot — no Python required from your side.
> Local-only. Blender must be installed and running on your machine. The bpy API only exists inside Blender's own Python — there is no cloud version.
> `execute_blender_code` is the primary tool. Almost everything you can do with the other 68 tools can also be done directly with execute_blender_code (which gives full bpy Python access). The specialized
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