Allows MCP clients to control Blender for 3D scene management, object manipulation, materials, rendering, geometry nodes, physics, and scripting via 55+ built-in tools.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@dcc-mcp-blender create a cube and change its color to blue"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AI agents should use the shared gateway through dcc-mcp-cli; IDE users may
continue to use the MCP endpoint. Prefer typed skills and tools over raw scripts.
dcc-mcp-cli is the preferred control path for every shell-capable agent. If
it is missing, ask the user before installing the latest official release:
# Linux/macOS
curl -fsSL https://raw.githubusercontent.com/dcc-mcp/dcc-mcp-core/main/scripts/install-cli.sh | sh
# Windows PowerShell
powershell -ExecutionPolicy Bypass -c "irm https://raw.githubusercontent.com/dcc-mcp/dcc-mcp-core/main/scripts/install-cli.ps1 | iex"Keep an official build current through the release manifest:
dcc-mcp-cli update check
dcc-mcp-cli update applyupdate apply downloads and stages the latest CLI for the next launch. It
does not update a running dcc-mcp-server; update that server in its own
environment.
dcc-mcp-cli dcc-types
dcc-mcp-cli list
dcc-mcp-cli search --query "<task>" --dcc-type blender
dcc-mcp-cli describe <tool-slug>
dcc-mcp-cli call <tool-slug> --json '{"key":"value"}'dcc-types reports release-catalog support; list reports live sessions. If a
tool belongs to an inactive progressive skill, call dcc-mcp-cli load-skill <skill-name> --dcc-type blender before retrying. For post-task improvement,
attach a stable session id with --meta-json, query dcc-mcp-cli stats --range 24h --session-id <task-id>, then pass the bounded evidence to the
review_skill_improvement prompt from dcc-mcp-skills-creator.
Blender addon for the DCC Model Context Protocol (MCP) ecosystem — embeds a Streamable HTTP MCP server directly inside Blender, letting any MCP-compatible AI client drive your 3D workflow.
Built through live dcc-mcp-blender calls with a baked Mantaflow/OpenVDB
nebula, Geometry Nodes particles, native PBR materials, four Cycles view layers,
and Blender Compositor finishing. The subtle Crab Nebula-derived point pass uses
NASA 3D Resources;
observe NASA media usage guidelines.
Related MCP server: blender-mcp
dcc-mcp-blender turns Blender into a first-class MCP server. Once the addon is enabled, any MCP client (Claude Desktop, custom agents, etc.) can call Blender tools over HTTP without any external gateway.
┌─────────────────────────────────┐
│ Blender (Python 3.10+) │
├─────────────────────────────────┤
│ dcc_mcp_blender │
│ ├─ BlenderMcpServer │
│ ├─ SkillCatalog (200+ tools) │
│ ├─ ActionRegistry │
│ └─ HTTP Handlers │
├─────────────────────────────────┤
│ dcc-mcp-core │
│ ├─ McpHttpServer │
│ ├─ JSON-RPC 2.0 │
│ └─ SSE Streaming │
└─────────────────────────────────┘
↓ http://127.0.0.1:9765/mcp (stable gateway)
┌─────────────────────────────────┐
│ MCP Host (Claude / etc.) │
└─────────────────────────────────┘
This live Blender 4.2 test moves from the imported mesh wireframe to a Cycles PBR beauty render, then rotates an HDRI and three-point light rig through 360° while a heavy particle rain simulation interacts with the sports car and wet ground. It exercises asset import, clearcoat and transmission materials, particle instancing and collision, depth of field, atmosphere, color management, lighting, animation, and final rendering through MCP.
Showcase assets: Car Concept by Darmstadt Graphics Group GmbH / Eric Chadwick (CC BY 4.0; Khronos logo trademark terms apply), Beach Parking HDRI by Poly Haven (CC0), and Easy Clouds (GPL-3.0-or-later).
Embedded MCP server — no external gateway needed; the server runs inside Blender's Python interpreter
200+ pre-built tools — scene management, object manipulation, mesh/UV editing, rigging, pose libraries, interchange, materials, node graphs, rendering, physics, scripting, cross-DCC import and more
Extensible skill system — drop new skill folders alongside built-ins or point to them via env vars
Main-thread host adapter — GUI mode uses core HostUiDispatcherBase semantics through BlenderUiDispatcher; headless mode uses BlenderHost with a core BlockingDispatcher
Streamable HTTP transport — compatible with any MCP 2025-03-26 client
Claude Desktop ready — ship a one-line mcpServers config and you're done
Category | Tools |
blender-scene |
|
blender-objects |
|
blender-mesh |
|
blender-mesh-ops |
|
blender-uv-ops |
|
blender-rigging |
|
blender-pose-library |
|
blender-import-to-scene |
|
blender-interchange |
|
blender-export-preset |
|
blender-shot-export |
|
blender-validation |
|
blender-pipeline |
|
blender-materials |
|
blender-shader-nodes |
|
blender-material-library |
|
blender-texture-bake |
|
blender-render |
|
blender-render-farm |
|
blender-scripting |
|
blender-dev |
|
blender-animation |
|
blender-lighting |
|
blender-light-rig |
|
blender-camera |
|
blender-collection |
|
blender-geometry |
|
blender-geometry-nodes |
|
blender-physics |
|
See src/dcc_mcp_blender/skills/SKILLS_INDEX.md for staged loading guidance, task-to-skill chains, and side-effect profiles for all bundled skills.
Want an AI agent to install the Blender-side dependencies, write the MCP host config, and walk you through enabling the add-on? Just ask your agent:
帮我参考 dcc-mcp/dcc-mcp-blender/install.md 去安装The agent follows install.md, which delegates the setup workflow
to skills/dcc-mcp-blender-setup. The remaining
options below are for manual installation.
Important: The release ZIP uses the Blender 4.2+ Extension format with
blender_manifest.tomlat the archive root and a flat package layout. Legacy add-on install (Edit → Preferences → Add-ons → Install) will fail with "ZIP packaged incorrectly;__init__.pyshould be in a directory, not at top-level". This is expected — use the Extensions path below. The Extension format is the only supported GUI installation path.
Download the latest platform ZIP from the Releases page:
dcc_mcp_blender_addon_win64_vX.Y.Z.zip, dcc_mcp_blender_addon_linux_vX.Y.Z.zip, or
dcc_mcp_blender_addon_macos_vX.Y.Z.zip
In Blender 4.2+: Edit → Preferences → Extensions → Install from Disk… → select the ZIP. (Do NOT use Edit → Preferences → Add-ons → Install — that legacy path is unsupported.)
Enable DCC MCP Blender
The MCP server starts on an OS-assigned instance port and registers with the local gateway.
Release ZIPs are Blender 4.2+ Extension packages. They include blender_manifest.toml and the matching dcc-mcp-core wheel under wheels/, so Blender installs the Python dependency into the extension's isolated environment.
The extension ZIP is assembled by packaging/assemble_zip.py. It resolves the latest compatible dcc-mcp-core wheel, places it under wheels/, and injects that wheel into blender_manifest.toml; Blender 4.2+ then installs it through the extension wheel mechanism instead of relying on global pip packages or sys.path edits. See packaging/release_smoke_checklist.md for the manual smoke test procedure.
pip install dcc-mcp-blenderThen in Blender's Python console:
import dcc_mcp_blender
dcc_mcp_blender.start_server()For CI or automation that needs Blender's main thread dispatcher:
blender --background --python src/dcc_mcp_blender/blender_bootstrap.pyThe bootstrap prints MCP_URL=..., discovers bundled skills, and drives BlenderHost in headless mode until the process is stopped.
In interactive add-on mode, BlenderUiDispatcher subclasses the shared core UI dispatcher and BlenderTimerPump
contains the Blender-specific bpy.app.timers wiring. In background mode, BlenderHost keeps using core
BlockingDispatcher with an explicit headless loop so automation does not depend on Blender UI timers.
Add to your claude_desktop_config.json:
{
"mcpServers": {
"blender": {
"url": "http://127.0.0.1:9765/mcp"
}
}
}Make sure the Blender addon is enabled and the server is running, then restart Claude Desktop.
import dcc_mcp_blender
# Start the server on an OS-assigned instance port
dcc_mcp_blender.start_server()
# Stop the server
dcc_mcp_blender.stop_server()Variable | Default | Description |
|
| Set to |
|
| Embedder backend for semantic recall. |
| (none) | Optional timeout in seconds for the readiness probe's dcc verification step. |
|
| Enable Prometheus |
| (auto) | Directory for render-job SQLite persistence; auto-resolves to platform tempdir when unset. |
|
| Raise on invalid skill YAML instead of logging a debug warning and skipping. |
|
| Enable workflow orchestration surface ( |
|
| Enable gateway failover for high-availability configurations. |
|
| Disable the |
|
| Disable arbitrary script execution; implies |
| (none) | Set to |
| (none) | Set to |
| (none) | Additional |
| (none) | Shared across all DCC-MCP packages; skill-path search falls back here when the Blender-specific var is unset. |
# Enable hybrid BM25 + vector recall
export DCC_MCP_BLENDER_SEMANTIC_INDEX=1
# Optional: use ONNX for dense embeddings (better semantic matching)
pip install 'dcc-mcp-core[semantic]'
export DCC_MCP_BLENDER_SEMANTIC_EMBEDDER=onnxWhen enabled, skill search results include a [semantic] extra field and RRF-fused scores.
The feature is opt-in — BM25-only recall remains the default and is not affected when the
env var is unset.
git clone https://github.com/dcc-mcp/dcc-mcp-blender
cd dcc-mcp-blender
pip install -e ".[dev]"
pytestMIT — see LICENSE for details.
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