blender-mcp: A Socket-Based Bridge for Driving Blender from Any LLM
Community plugin to control Blender 3D with any LLM of your choice
At a glance
- What is it?
- This community plugin connects Blender 3D to LLMs via the Model Context Protocol, using a Python server and a Blender addon. It enables prompt-driven object creation, scene inspection, and arbitrary Python execution, but requires careful setup and carries real security risks.
- Who is it for?
- Adopt blender-mcp if you are a Blender user who wants to experiment with prompt-driven modeling and already use an MCP-compatible client like Claude Desktop or Cursor. Skip it if you need a production-grade tool with formal support, or if you cannot accept the risk of arbitrary Python code execution in Blender.
- Can I use it commercially?
- Yes. MIT is a permissive licence: you can use, modify and sell software built on it, as long as you keep its copyright and licence notices.
- Is it still maintained?
- Yes. The repository received new commits within the last day.
- What is it written in?
- Mainly Python, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on November 13, 2026, and from our analysis. They are not legal advice.
Star history
- ahujasid/blender-mcp34,304 ★ · +6,221
| Repository | 2026-09-10 | 2026-11-13 |
|---|---|---|
| ahujasid/blender-mcp | 28.1k | 34.3k |
6,221 Stars in the last 64 days, measured from the daily GitHub snapshot. Compare with other projects
Editorial analysis
What Problem Does blender-mcp Solve?
Blender is a powerful but complex 3D modeling tool. Its interface has a steep learning curve, and many repetitive tasks, such as creating primitive objects, adjusting materials, or inspecting scene hierarchies, require navigating menus and panels. blender-mcp aims to replace that manual interaction with natural language prompts. It is a community plugin, not an official Blender feature, that lets you ask an LLM like Claude to build or modify a scene. The target user is someone who already uses an MCP-compatible client and wants to speed up their Blender workflow without learning every hotkey. The README positions it as a bridge: the LLM sends commands, the plugin executes them in Blender, and the results are sent back.
Architecture: Two Components, One Socket Connection
The system is split into two distinct pieces. The first is a Blender addon, `addon.py`, which creates a socket server inside Blender. That server listens for incoming commands and executes them. The second is a Python MCP server, `src/blender_mcp/server.py`, which implements the Model Context Protocol and connects to the Blender addon. The MCP server is what your LLM client talks to, using the standard MCP protocol. The addon and server communicate over a socket, which means the LLM client does not directly touch Blender. This separation is important because Blender runs its own Python interpreter, and the addon must live inside that environment. The README describes this as two-way communication: commands flow from the LLM to Blender, and scene information flows back. This design is typical for MCP integrations, but it introduces a moving part: if the socket connection drops, the LLM has no way to reach Blender.
Getting It Running: uv, a Client, and a Blender Addon
The README's one-command installer sets up your AI apps and the Blender addon; the manual setup is three steps. First, install `uv`, the Python package manager. The README is emphatic: use the official installer, not `pip install uv`. Second, point your MCP client at the server. For Claude Desktop, you edit its config JSON to add a server entry with `"command": "uvx"` and `"args": ["mcp-for-blender"]`. For Claude Code, the command is `claude mcp add blender uvx mcp-for-blender`. For Codex, it is `codex mcp add blender -- uvx mcp-for-blender`. Third, install the Blender addon by running `uvx mcp-for-blender install-addon`, then enable it in Blender under Edit → Preferences → Add-ons → Interface: MCP for Blender. Finally, in Blender's 3D viewport, press `N`, open the MCP tab, and click Start MCP Server. The README warns to run only one instance of the MCP server at a time, either in Cursor or Claude Desktop, not both. The README also has a section titled "Make your client find uvx" for clients that cannot locate the command.
Capabilities: From Primitives to AI-Generated Models
The feature list covers object manipulation: create, modify, and delete 3D objects. Material control lets you apply and change materials and colors. Scene inspection gives the LLM detailed information about the current scene, which is necessary for it to make informed changes. The most powerful and risky feature is code execution: the LLM can run arbitrary Python code in Blender. That is not a sandbox; it is full access to Blender's Python API. Beyond basic operations, the plugin can pull assets from Poly Haven, models from Sketchfab, and low-poly models from Poly Pizza. It also supports AI-generated 3D models via Meshy, Tripo, Hyper3D Rodin and Hunyuan3D, and a separate Premium option generates them without bringing your own API keys. For a user, this means the plugin is not just a command sender; it is a pipeline for bringing external assets into Blender.
Security and Failure Modes: What the README Warns About
The README has a "Limitations & Security Considerations" section. The obvious risk is arbitrary code execution. If your LLM client is compromised, or if you point it at a malicious prompt, it can run destructive Python in Blender. This is not a theoretical issue; it is inherent to the design. The README also mentions telemetry control, meaning the plugin may collect usage data, and you can disable it. On the failure side, the README has a section on making your client find `uvx`. Another failure mode is running multiple server instances, which the README explicitly warns against. The socket connection itself is also a point of failure, and the README says to click Start MCP Server in the MCP for Blender tab if the server is not running.
Alternatives: Comparing Approaches to AI-Assisted 3D
The main alternative is to use Blender's built-in Python scripting without an MCP layer. You can write scripts that manipulate the scene and run them from Blender's text editor or command line. That approach gives you full control and does not depend on an external LLM client. The difference is that scripting requires you to know Blender's Python API and to formulate commands yourself. blender-mcp moves that burden to the LLM, but it adds a dependency on an MCP client and a socket server. Another alternative is a specialized AI plugin that generates models directly. Those tools often have their own UI and do not require a general-purpose LLM. The trade-off is that they are narrower in scope. blender-mcp is general, but it inherits the LLM's unpredictability. A wrong prompt can produce a wrong object, and you need to inspect the result visually.
Maintenance and Upgrade Cost
The repository publishes no releases, but the last push was October 2026, which suggests active development. The README includes an "Upgrading (existing users)" section. Because the plugin depends on `uv` and `uvx`, you need to keep those up to date as well. The license is MIT, which means you can modify and redistribute it freely, but there is no warranty. The project is a community effort, not affiliated with Blender, so support comes from the community, with a Discord server and GitHub issues linked. The maintenance cost for a user is moderate: you must track changes to the MCP server and the addon, and ensure they stay compatible with your Blender version. Newer Blender releases may introduce breaking changes.
Editorial conclusion
Adopt blender-mcp if you are a Blender user who wants to experiment with prompt-driven modeling and already use an MCP-compatible client like Claude Desktop or Cursor. Skip it if you need a production-grade tool with formal support, or if you cannot accept the risk of arbitrary Python code execution in Blender. Before adopting, verify that your Blender version works with the addon, that uv is installed via the official installer, and that your MCP client can find uvx. Also review the telemetry control settings and understand that running the server exposes Blender to commands from your LLM client, so use it only in trusted environments.
Frequently asked questions
What does MCP for Blender do?
It connects an LLM client to Blender over a socket-based server for two-way communication. The listed capabilities are creating, modifying and deleting 3D objects, applying and modifying materials and colors, reading the current scene, running arbitrary Python code in Blender, and fetching assets from Poly Haven, Sketchfab, Poly Pizza, Hyper3D Rodin and Hunyuan3D.
How do I install MCP for Blender?
Run the one-line installer, `curl -LsSf https://www.mcp-for-blender.com/install.sh | sh` on macOS or Linux, which installs uv if needed, finds your MCP clients and installs the Blender addon. If you already have uv, `uvx mcp-for-blender setup` does the same work. Then fully quit and reopen your AI app and open Blender.
How do I install the MCP for Blender addon by hand?
Run `uvx mcp-for-blender install-addon`, then in Blender open Edit, Preferences, Add-ons and enable Interface: MCP for Blender. The addon starts its server when Blender opens, and you can confirm it by pressing N in the 3D viewport to open the MCP for Blender tab.
How do I turn on MCP in Blender?
Blender ships no such feature, since the project states it is a third-party integration and not made by Blender. You enable it by installing the addon, turning on Interface: MCP for Blender in the add-ons preferences, and clicking Start MCP Server in the MCP for Blender tab of the sidebar.
Is MCP for Blender free?
The code is MIT licensed and the setup path is free, including the one-line installer and the addon. A Premium option is offered separately for generating AI 3D models with Hunyuan3D, Tripo and Hyper3D Rodin without supplying your own API keys.
Does Blender have an MCP server?
Not from Blender itself. The project is a community integration built as two parts, an addon that opens a socket server inside Blender and a separate MCP server in src/blender_mcp/server.py that the AI client connects to.
Official sources
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