ageless-h

ageless-h / blender-mcp

Public

MCP server integration for AI-assisted Blender automation. Features a 4-layer architecture with 26 specialized tools for deep scene perception, node editing, and imperative control.

github.comageless-hblender-mcp
2
0
100% credibility
Found Feb 12, 2026 at 1 stars 2x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Blender MCP connects AI coding assistants to Blender, letting them read scene data and automate modeling, materials, animation, and rendering with 26 safe tools.

How It Works

1
🔍 Discover AI Magic for Blender

You hear about a helpful tool that lets AI assistants like your coding buddy create 3D models in Blender automatically.

2
📥 Add the Helper to Blender

You copy a simple folder into Blender's addons area, restart Blender, search for 'Blender MCP', and turn it on.

3
⚙️ Start the Bridge

In Blender's side panel, you click 'Start Server' – now your AI can talk to Blender safely.

4
🔗 Tell Your AI Friend

In your AI chat like Cursor or Claude, you mention using Blender MCP, and it connects instantly.

5
🎨 Watch AI Build Your Scene

You describe 'make a shiny car on a road', and the AI reads your scene, adds objects, lights, materials – everything appears live in Blender!

6
👀 Check and Tweak

You glance at the viewport screenshot from AI, make tiny changes in Blender if needed, and ask AI to refine.

✨ Stunning 3D Art Ready

Your complex model is complete, rendered beautifully – AI handled the hard parts, you feel like a pro artist!

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AI-Generated Review

What is blender-mcp?

Blender-mcp is a Python MCP server and Blender addon that lets AI models automate 3D scene creation via the Model Context Protocol. Install the blender mcp addon in Blender 4.2+, start the blender mcp server with `uvx ageless-blender-mcp`, and connect tools like Claude, Copilot in VSCode, or Ollama. It exposes 26 specialized tools across perception (read scene state), declarative edits (nodes/animation), imperative control (objects/modifiers), and fallbacks (operators/scripts), solving repetitive manual modeling tasks.

Why is it gaining traction?

This blender mcp github repo stands out with its layered 26-tool architecture—start with read-only perception to avoid mistakes, then precise writes—unlike raw bpy scripting or basic addons. It plugs into 18+ MCP clients (Claude blender mcp github, mcp github copilot vscode/intellij, ChatGPT, n8n), with quick JSON examples and a blender mcp tutorial in the README. Low-latency socket comms and security guardrails make AI feel native in Blender workflows.

Who should use this?

3D artists prototyping scenes with AI prompts in Claude or Copilot; pipeline devs automating Blender-mcp ChatGPT asset generation; motion designers scripting node graphs or animations via natural language. Ideal for blender mcprep fans wanting AI over manual ops.

Verdict

Worth a spin for AI-Blender experiments—solid PyPI install, client docs, and real-Blender tests—but at 28 stars and 1.0% credibility score, it's early MVP with mcp github issues to watch. Pair with the blender mcp server github for production tweaks. (187 words)

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