ellmos Blender Use MCP

🇩🇪 Deutsche Version

Part of the ellmos-ai family.

📦 View on npm → | 🛡️ Security Policy | 🤖 LLM Context | 🌐 Ecosystem

An asset-QA tool for game and 3D asset pipelines: verify that an exported FBX actually reimports cleanly in headless Blender — mesh count, material count, and required naming prefixes checked automatically, with a deterministic JSON result instead of a manual eyeball pass. blender_verify_fbx_reimport is the core tool; blender_locate and blender_run_script are the general-purpose primitives it is built on.

No add-on. No TCP port. No background daemon. This server does not install anything into Blender, does not open a socket for a running Blender instance to connect to, and does not keep Blender resident. Each call spawns blender --background --python <script.py>, waits for a bounded, timeout-guarded exit, and returns the result — headless and stateless by design. It does not download assets and does not collect telemetry.

How this differs from other Blender MCP servers. Most Blender MCP projects (e.g. ahujasid/blender-mcp, the official Blender Labs MCP server) drive a live, running Blender GUI over a TCP/add-on bridge for interactive scene editing — a different use case with a different trust model (an open socket, an installed add-on, a persistent process). This server instead targets CI-style, one-shot asset verification: run it in a pipeline step, get a pass/fail JSON, move on. If you need live GUI control, use a reviewed Blender MCP add-on separately (see Safety below).

Architecture & Workflow

1. Component Topology

graph TD
    subgraph Client ["AI Assistant & Client Environment"]
        AI["AI Agent (Claude / Codex / Gemini)"]
        Config["MCP Configuration (npx / node)"]
    end

    subgraph Server ["ellmos Blender Use MCP Server"]
        MCP["MCP Protocol Server (src/index.js)"]
        subgraph Tools ["Tool Handlers"]
            T1["blender_verify_fbx_reimport"]
            T2["blender_run_script"]
            T3["blender_locate"]
        end
        Safety["Timeout & Tail Buffer Guard (8k chars)"]
    end

    subgraph Subprocess ["Headless Subprocess (Isolated)"]
        Exe["Blender Executable (blender --background)"]
        Python["Temp Python Verification Script"]
        FBX["Target FBX Asset File"]
        JSONOut["Deterministic JSON Result"]
    end

    AI -->|JSON-RPC Request| MCP
    MCP --> Tools
    T1 -->|Generates script & spawns| Exe
    T2 -->|Executes arbitrary python| Exe
    T3 -->|Locates binary| Exe
    Exe --> Python
    Python --> FBX
    FBX -->|Mesh / Material / Naming QA| JSONOut
    JSONOut --> Safety
    Safety -->|Bounded Response| AI

    style Client fill:#1e1e2e,stroke:#89b4fa,stroke-width:1px
    style Server fill:#181825,stroke:#cba6f7,stroke-width:1px
    style Subprocess fill:#11111b,stroke:#a6e3a1,stroke-width:1px

2. Headless Asset-QA Verification Lifecycle

sequenceDiagram
    autonumber
    actor Client as AI Assistant / CI Pipeline
    participant Server as ellmos Blender Use MCP
    participant Resolver as Blender Resolver
    participant Process as Headless Subprocess
    participant Python as Blender Python Engine
    participant FS as Local Filesystem (FBX)

    Client->>Server: Call blender_verify_fbx_reimport(fbxPath, requiredPrefixes)
    Server->>Resolver: Resolve Blender Executable (blender_locate / BLENDER_EXE / Registry / PATH)
    Resolver-->>Server: Return Validated Executable Path
    Server->>FS: Write Temp Python Verification Script
    Server->>Process: Spawn blender --background --python <script> (timeout-guarded)
    Process->>Python: Execute Verification Script
    Python->>FS: bpy.ops.import_scene.fbx(filepath=fbxPath)
    FS-->>Python: Parse Mesh Objects & Material Slots
    Python->>Python: Validate Naming Prefixes, Object Counts & Hierarchy
    Python->>FS: Write Output JSON Verification Result
    Process-->>Server: Process Exit (Exit Code 0 / Bounded Tail Buffer)
    Server->>FS: Read Result & Clean Up Temp Verification Script
    Server-->>Client: Deterministic JSON Result (meshCount, materialCount, missingPrefixes, ok)

Related MCP server: Blender MCP Server

Tools

Safety

• This server runs local Python inside Blender. Use only scripts and asset paths you trust.

• The default timeout is bounded.

• No remote asset marketplaces, API keys, or telemetry are included.

• For live GUI control, use a reviewed Blender MCP add-on separately.

Installation

Option 1: Run via npx (no install)

{
  "mcpServers": {
    "blender-use": {
      "command": "npx",
      "args": ["-y", "ellmos-blender-use-mcp"]
    }
  }
}

Option 2: Install from source

git clone https://github.com/ellmos-ai/ellmos-blender-use-mcp.git
cd ellmos-blender-use-mcp
npm install
npm run build
node src/index.js

For a local checkout, point command/args at the cloned src/index.js instead:

{
  "mcpServers": {
    "blender-use": {
      "command": "node",
      "args": ["<path-to-repo>/src/index.js"]
    }
  }
}

Configuration

• BLENDER_EXE — optional path to the Blender executable. Without it, tools try the explicit blenderPath argument, then BLENDER_EXE, then the standard Blender install locations on Windows (%ProgramFiles%\Blender Foundation\Blender <version>\blender.exe and the equivalent 32-bit and per-user roots, newest version first), then PATH. On Linux and macOS the lookup goes straight from BLENDER_EXE to PATH.

• Every tool also accepts an explicit blenderPath argument per call, which takes priority over BLENDER_EXE.

• Process output is retained only as a tail: blender_run_script defaults to 8,000 characters (configurable up to 50,000); FBX verification keeps 8,000. The response marks outputTruncated: true when earlier output was discarded, so verbose Blender scripts cannot grow the MCP process memory without bound.

License

MIT — see LICENSE.

ellmos-ai Ecosystem

This MCP server is part of the ellmos-ai ecosystem — AI infrastructure, MCP servers, and intelligent tools.

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