About three.ws Blender
three.ws Blender is an MCP server that lets an AI assistant drive a local Blender in headless mode to inspect, convert, render and script 3D files. Rendered previews return inline, so the assistant can view the model without filesystem access.
Key features
- 01Inspect objects, materials, textures and animations in 3D files
- 02Convert between GLB, FBX, OBJ, USD and other formats
- 03Auto-framed, auto-lit multi-view preview renders
- 04Optimize triangle counts, texture sizes and compression
- 05Run bpy scripts and generate models from text or images
Use cases
- 01Converting a client FBX into a web-ready GLB with fewer triangles
- 02Rendering model previews on servers or CI without a display
- 03Letting an assistant check the look of an imported or generated model
MCP support
The server exposes Blender tools to MCP clients for scene inspection, conversion, rendering, script execution and model generation. Rendered images are returned inline to the client.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y @three-ws/blender-mcpBLENDER_PATHAbsolute path to the Blender 3.0+ executable. Leave unset to discover it on PATH and at the platform's standard install locations.BLENDER_MCP_TIMEOUT_MSCeiling for one Blender job in milliseconds. Renders and heavy conversions are the slow ones.BLENDER_MCP_WORKDIRDirectory for outputs written when a tool is called without an explicit output path.BLENDER_MCP_ALLOW_PYTHONSet to 0 to withdraw blender_run_python, which executes caller-supplied Python inside Blender, from the advertised tool list.BLENDER_MCP_INLINE_IMAGE_BYTESCeiling on inlined image bytes. Past this the image stays on disk and the response says where.BLENDER_MCP_INLINE_IMAGE_PXLongest edge of the render copy returned inline in a tool result. The full-resolution PNG is always written to disk.BLENDER_MCP_MAX_CONCURRENCYHow many Blender processes may run at once. Further calls queue rather than compete for memory.THREE_WS_BASEBase URL of the three.ws deployment backing blender_forge_import.THREE_WS_FORGE_TIMEOUT_MSCeiling for one text-to-3D generation in milliseconds.THREE_WS_FORGE_PROVIDER_KEYSecretMeshy/Tripo API key for the bring-your-own-key geometry lane. The default image lane is free and needs no key.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
7Saved tool list · updated 2w ago
This tool takes no parameters.
Details
From the project README@three-ws/blender-mcp
Give any AI agent the Blender on your machine. Headless, no GUI, no add-on to install.
A Model Context Protocol server that hands an AI assistant a real Blender over stdio. Inspect a 3D file, convert between GLB, glTF, FBX, OBJ, STL, PLY, Collada, Alembic, USD and
.blend, render an auto-framed and auto-lit preview that comes back inline so the assistant can see it, run abpyscript against a scene, and generate a model from a text prompt on the free three.ws Forge lane.
Blender runs in background mode (blender -b), one process per call. That means it works on a server, in CI, and inside a container with no display, no GUI session to keep alive, and no add-on to install into Blender first. Everything is real: each tool drives the Blender installed on the machine, and blender_forge_import calls the live public three.ws generation pipeline.
Requirements
- Node.js 20+
- Blender 3.0 or newer, installed locally. Download it, or install it from your package manager. If it is not on
PATH, setBLENDER_PATHto the executable (/Applications/Blender.app/Contents/MacOS/Blenderon macOS).
Call blender_info first if anything misbehaves: it reports the exact executable, version, render engines, and file formats this build supports.
Install
npm install @three-ws/blender-mcp
Or run it with npx (no install):
npx -y @three-ws/blender-mcp
Claude Code
claude mcp add blender -- npx -y @three-ws/blender-mcp
Claude Desktop / Cursor
Paste this into your MCP config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows):
{
"mcpServers": {
"blender": {
"command": "npx",
"args": ["-y", "@three-ws/blender-mcp"]
}
}
}
Add "env": { "BLENDER_PATH": "/path/to/blender" } if Blender is not on PATH.
Tools
| Tool | What it does |
|---|---|
blender_info | Reports the Blender being driven: path, version, bundled Python, usable render engines, and the import/export formats this build actually supports. Read-only. |
blender_scene_info | Opens a 3D file and describes it: objects with types, parents, dimensions and modifiers; evaluated triangle and vertex counts; materials; a texture inventory with each image's resolution and byte size; armature bone names; animation actions with frame ranges; world-space bounds. Read-only. |
blender_convert | Imports one format and exports another, chosen by the file extensions. Applies modifiers by default and can bake in a uniform unit scale. The exact format list depends on the build (some Linux packages ship without USD, Collada, or Alembic), and blender_info reports what yours actually has. |
blender_optimize | The delivery pass in one call: decimate to a triangle budget, scale oversized textures, purge unreferenced datablocks, and compress the mesh streams with meshopt or Draco. Reports before and after triangles, texture bytes and file size. |
blender_render | Renders a still PNG and returns it inline, so the assistant can actually see the model in one call even with no filesystem access. Ask for several views and it orbits the model, every angle in the same launch. If the file has no camera, one is created and framed to the model's bounding sphere; if it has no light, a key light and a lit world are added. A scene that already has its own camera and lighting renders as authored. |
blender_run_python | Runs a bpy script against a scene, optionally opening a file first and exporting the result afterwards. The escape hatch for anything the other tools do not cover. |
blender_forge_import | Generates a model from a text prompt or a reference image on the public three.ws Forge pipeline and brings it into Blender, converting on the way in if the output asks for another format. The default lane is free. |
Examples
Describe a file before touching it:
> What is in ~/assets/character.fbx?
blender_scene_info { "input": "~/assets/character.fbx" }
→ 4 meshes, 41,208 triangles, 1 armature (67 bones), 3 actions, bounds 1.78m tall
Make a model shippable and see what it cost:
blender_optimize { "input": "character.glb", "output": "character-web.glb", "max_triangles": 30000, "max_texture_px": 1024 }
→ 4.1 MB to 780 KB (81% saved): 96,412 to 30,000 triangles, textures 2048 to 1024, meshopt compressed
Look at it from four sides at once:
blender_render { "input": "character-web.glb", "views": 4 }
Convert a client's FBX into a web-ready GLB, in metres:
blender_convert { "input": "character.fbx", "output": "character.glb", "scale": 0.01 }
See what you just made:
blender_render { "input": "character.glb", "output": "preview.png", "samples": 64 }
Halve the triangle count and export in one call:
blender_run_python {
"input": "character.glb",
"output": "character-lod1.glb",
"code": "import bpy\nfor obj in bpy.data.objects:\n if obj.type == 'MESH':\n obj.modifiers.new('Decimate', 'DECIMATE').ratio = 0.5\nresult = {'meshes': len([o for o in bpy.data.objects if o.type == 'MESH'])}"
}
Generate an asset and open it as a .blend:
blender_forge_import { "prompt": "a weathered brass diving helmet", "output": "helmet.blend" }
Or reconstruct one from a reference image:
blender_forge_import { "image": "./reference.png", "prompt": "a brass diving helmet", "output": "helmet.glb" }
Compressed glTF
Meshopt- and Draco-compressed assets are decoded automatically before Blender opens them, in process, with no external binary to install.
This is not a nicety. Blender's glTF importer has no decoder for EXT_meshopt_compression, which is what gltfpack emits and what most three.ws avatars are delivered as; handed one it fails outright with "Extension EXT_meshopt_compression is not available on this addon version". Draco is nominally supported but only on builds that ship libextern_draco, which several Linux distribution packages do not. Every tool that takes an input goes through the same decode, and the response names what was decoded in decoded_compression. Your file is never modified: the decoded copy lives in the job's scratch directory and is deleted with it.
How a call works
Every tool call spawns blender -b --factory-startup --python src/py/runner.py -- <job.json> <result.json> and exits. Three consequences worth knowing:
--factory-startupkeeps your saved preferences and third-party add-ons out of the result, so a conversion produces the same file on any machine.- The runner writes its payload to a file, never to stdout. Blender prints progress, add-on chatter, and render statistics on stdout, and picking a payload out of that stream is guesswork. A missing result file therefore means Blender died, and the error carries the log tail that says why.
- One process per call. A crashed job cannot corrupt the next one, and nothing stays resident between calls.
Failures come back as structured tool errors (input_not_found, format_unsupported, engine_unavailable, timeout, blender_not_found, blender_unusable, blender_crashed), each with a message that says what to do about it. blender_not_found means no candidate exists; blender_unusable means one exists but would not run, and carries the per-candidate diagnostics, because on a loaded machine a failed probe is transient and telling you to install software you already have is the wrong answer.
Environment variables
| Variable | Default | Purpose |
|---|---|---|
BLENDER_PATH | discovered on PATH and at the platform's standard install locations | Absolute path to the Blender executable. |
BLENDER_MCP_TIMEOUT_MS | 300000 | Ceiling for one Blender job. |
BLENDER_MCP_WORKDIR | <tmpdir>/three-ws-blender-mcp | Where outputs land when a tool is called without an explicit output path. |
BLENDER_MCP_ALLOW_PYTHON | 1 | Set to 0 to withdraw blender_run_python from the advertised tool list entirely. |
BLENDER_MCP_MAX_CONCURRENCY | 2 | Blender processes allowed at once. Further calls queue rather than compete for memory. |
BLENDER_MCP_INLINE_IMAGE_PX | 768 | Longest edge of the render copy returned inline. The full-resolution PNG always goes to disk. |
BLENDER_MCP_INLINE_IMAGE_BYTES | 1500000 | Past this the image stays on disk and the response says so. |
THREE_WS_BASE | https://three.ws | Deployment backing blender_forge_import. |
THREE_WS_FORGE_TIMEOUT_MS | 600000 | Ceiling for one text-to-3D generation. |
THREE_WS_FORGE_PROVIDER_KEY | unset | Meshy/Tripo key for the bring-your-own-key geometry lane. The default image lane is free and needs no key. |
Security
blender_run_python executes caller-supplied Python inside Blender with the permissions of this server: it can read and write the local filesystem. That is the point of the tool, and it is annotated destructiveHint: true so a client can prompt before running it. For unattended or shared deployments, set BLENDER_MCP_ALLOW_PYTHON=0 and the tool is never advertised.
Everything else stays local. Only blender_forge_import reaches the network, and only to the three.ws deployment named by THREE_WS_BASE.
Development
node src/index.js # run the server over stdio
npm test # offline invariants + real-Blender integration
npm run inspect # open the MCP Inspector against it
test/registration.test.mjs runs offline and passes with no Blender installed. test/blender-session.test.mjs drives the server through a real MCP stdio session against the local Blender, building its fixture with Blender itself; it skips cleanly when no Blender is present.
Related
integrations/blender/is the artist-facing counterpart: a Blender add-on with a sidebar panel that generates three.ws models from inside the GUI. This package is the agent-facing one.@three-ws/scene-mcpcomposes whole 3D worlds from a sentence.- three.ws is the platform behind the Forge pipeline.
License
Apache-2.0
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.