DCC-MCP-IPC
Allows interaction with Blender via RPyC transport, enabling AI agents to execute commands, manage scenes, and register skills for automated tasks within Blender.
Allows interaction with Houdini via RPyC transport, enabling AI agents to execute commands, manage scenes, and register skills for automated tasks within Houdini.
Allows interaction with Unity via HTTP transport, enabling AI agents to execute commands, manage scenes, and register skills for automated tasks within Unity.
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-IPClist all available skills in Maya"
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.
DCC-MCP-IPC
Multi-protocol IPC adapter layer for DCC software integration with Model Context Protocol (MCP).
Built on top of dcc-mcp-core (Rust/PyO3 backend), it provides a high-performance, type-safe framework for exposing DCC functionality as MCP tools across multiple transport protocols.
Documentation: docs site | v2.0.0 (Unreleased) — Breaking changes ahead, see CHANGELOG.md
Why DCC-MCP-IPC?
Feature | Description |
Protocol-agnostic | RPyC for embedded-Python DCCs (Maya/Houdini/Blender), HTTP for Unreal/Unity, WebSocket, and Rust-native IPC for maximum throughput. |
Zero-code Skills | Drop a |
Rust-powered core | Action dispatch, validation, and telemetry handled by dcc-mcp-core via PyO3; Python layer focuses on DCC-specific glue code. |
Hot-reload skills |
|
Service discovery | ZeroConf (mDNS) + file-based fallback for automatic DCC server detection. |
Connection pooling |
|
Features
Thread-safe RPyC / HTTP / WebSocket / Rust-native IPC server implementations
Skills system — zero-code MCP tool registration from
SKILL.mdfrontmatter with hot-reloadAction system backed by
ActionRegistry+ActionDispatcher(Rust) — JSON-serialised parameter dispatchTransport factory — pluggable transport layer (
rpyc,http,websocket,ipc)Service discovery: ZeroConf (mDNS) + file-based fallback via
ServiceDiscoveryFactoryAsync client (
asyncio) for non-blocking operationsAbstract base classes for creating DCC-specific adapters (
DCCAdapter) and servicesApplication adapter pattern for generic app integration
Scene & snapshot interfaces over RPyC and HTTP transports
Mock DCC services for testing without actual DCC applications
Comprehensive error handling with custom exception hierarchy
Architecture
graph TD
A[AI Assistant / MCP Client] --> B[MCP Server Layer]
B --> C[ActionAdapter\nActionRegistry + ActionDispatcher]
C --> D[RPyC Transport\nDCC Python env]
C --> E[IPC Transport\nRust FramedChannel]
C --> F[HTTP Transport\nUnreal / Unity REST]
C --> G[WebSocket Transport]
G[SkillManager\nSKILL.md auto-discovery] --> C
H[dcc-mcp-core\nRust/PyO3 backend] --> C
D --> I[DCC App\nMaya / Houdini / Blender]
E --> I
F --> J[DCC App\nUnreal / Unity]
style C fill:#e1f5fe
style H fill:#fff3e0
style G fill:#e8f5e9Key Components
Component | Module | Description |
|
| Wraps Rust |
|
| Scans directories for |
|
| Manages the RPyC/IPC server lifecycle inside a DCC process |
|
| Core client connection/call logic with auto-discovery |
|
| Connection pooling for efficient resource management |
|
| Rust-native framed-channel IPC, registered as |
|
| Strategy-pattern selector for ZeroConf or file-based discovery |
|
| Simulates DCC applications for testing |
Installation
pip install dcc-mcp-ipcWith optional ZeroConf support:
pip install "dcc-mcp-ipc[zeroconf]"Or with Poetry:
poetry add dcc-mcp-ipcRequirements
Python >= 3.8 (< 4.0)
dcc-mcp-core >= 0.12.0 (< 1.0.0)
rpyc >= 6.0.0 (< 7.0.0)
Optional: zeroconf >= 0.38.0 for mDNS discovery
Quick Start
Server-side (within DCC application)
<augment_code_snippet path="README.md" mode="EXCERPT">
from dcc_mcp_ipc.server import create_dcc_server, DCCRPyCService
class MayaService(DCCRPyCService):
def get_scene_info(self):
return {"scene": "Maya scene info"}
def exposed_execute_cmd(self, cmd_name, *args, **kwargs):
pass
server = create_dcc_server(
dcc_name="maya",
service_class=MayaService,
port=18812,
)
server.start(threaded=True)</augment_code_snippet>
Client-side
<augment_code_snippet path="README.md" mode="EXCERPT">
from dcc_mcp_ipc.client import BaseDCCClient
client = BaseDCCClient("maya", host="localhost", port=18812)
client.connect()
result = client.call("get_scene_info")
client.disconnect()</augment_code_snippet>
Usage Guide
Action System (v2.0.0+)
The Action system is built on the Rust-backed ActionRegistry + ActionDispatcher. All parameters are JSON-serialised:
<augment_code_snippet path="README.md" mode="EXCERPT">
from dcc_mcp_ipc.action_adapter import ActionAdapter, get_action_adapter
adapter = get_action_adapter("maya")
def create_sphere(radius: float = 1.0, name: str = "sphere1") -> dict:
return {"success": True, "message": f"Created {name}", "context": {"name": name}}
adapter.register_action(
"create_sphere",
create_sphere,
description="Create a sphere primitive",
category="modeling",
tags=["primitive", "mesh"],
)
result = adapter.call_action("create_sphere", radius=2.0, name="mySphere")
print(result.success) # True
print(result.to_dict()) # {"success": True, ...}</augment_code_snippet>
Zero-code Skills via SkillManager
Drop a SKILL.md file into a directory structure:
my_skills/
create_light/
SKILL.md # frontmatter: name, description, tools, scripts
run.py # executed when the tool is called<augment_code_snippet path="README.md" mode="EXCERPT">
from dcc_mcp_ipc.skills import SkillManager
from dcc_mcp_ipc.action_adapter import get_action_adapter
adapter = get_action_adapter("maya")
mgr = SkillManager(adapter=adapter, dcc_name="maya")
mgr.load_paths(["/pipeline/skills"])
mgr.start_watching()
# Now "create_light" is callable as an MCP tool
result = adapter.call_action("create_light", intensity=100.0)</augment_code_snippet>
Connection Pool
<augment_code_snippet path="README.md" mode="EXCERPT">
from dcc_mcp_ipc.client import ConnectionPool
pool = ConnectionPool()
with pool.get_client("maya", host="localhost") as client:
result = client.call("execute_cmd", "sphere", radius=5)
print(result)</augment_code_snippet>
Service Factories
Three factory patterns are available for different lifecycle needs:
<augment_code_snippet path="README.md" mode="EXCERPT">
from dcc_mcp_ipc.server import (
create_service_factory,
create_shared_service_instance,
create_raw_threaded_server,
)
class SceneManager:
def __init__(self):
self.scenes = {}
def add_scene(self, name, data):
self.scenes[name] = data
scene_manager = SceneManager()
# Per-connection instance
service_factory = create_service_factory(MayaService, scene_manager)
# Shared singleton instance
shared_service = create_shared_service_instance(MayaService, scene_manager)
# Raw threaded server
server = create_raw_threaded_server(service_factory, port=18812)
server.start()</augment_code_snippet>
Rust-native IPC Transport
Zero-copy low-latency messaging via the Rust core:
<augment_code_snippet path="README.md" mode="EXCERPT">
import os
from dcc_mcp_core import TransportAddress
from dcc_mcp_ipc.transport.ipc_transport import (
IpcClientTransport,
IpcServerTransport,
IpcTransportConfig,
)
# Client side
config = IpcTransportConfig(host="localhost", port=19000)
transport = IpcClientTransport(config)
transport.connect()
result = transport.execute("get_scene_info")
transport.disconnect()
# Server side (inside DCC plugin)
def handle_channel(channel):
msg = channel.recv()
# process and respond ...
addr = TransportAddress.default_local("maya", os.getpid())
server = IpcServerTransport(addr, handler=handle_channel)
bound_addr = server.start()</augment_code_snippet>
Creating a Custom DCC Adapter
<augment_code_snippet path="README.md" mode="EXCERPT">
from dcc_mcp_ipc.adapter import DCCAdapter
from dcc_mcp_ipc.client import BaseDCCClient
class MayaAdapter(DCCAdapter):
def _initialize_client(self) -> None:
self.client = BaseDCCClient(
dcc_name="maya",
host=self.host,
port=self.port,
connection_timeout=self.connection_timeout,
)
def create_sphere(self, radius: float = 1.0):
self.ensure_connected()
assert self.client is not None
return self.client.execute_dcc_command(f"sphere -r {radius};")</augment_code_snippet>
Async Client
<augment_code_snippet path="README.md" mode="EXCERPT">
import asyncio
from dcc_mcp_ipc.client.async_dcc import AsyncDCCClient
async def main():
client = AsyncDCCClient("maya", host="localhost", port=18812)
await client.connect()
result = await client.call("get_scene_info")
await client.disconnect()
asyncio.run(main())</augment_code_snippet>
Testing with Mock Services
<augment_code_snippet path="README.md" mode="EXCERPT">
import threading
from dcc_mcp_ipc.testing.mock_services import MockDCCService
from dcc_mcp_ipc.client import BaseDCCClient
server = MockDCCService.start(port=18812)
client = BaseDCCClient("mock_dcc", host="localhost", port=18812)
client.connect()
info = client.get_dcc_info()
print(info) # {"name": "mock_dcc", ...}
client.disconnect()
server.stop()</augment_code_snippet>
Development
Setup
git clone https://github.com/loonghao/dcc-mcp-ipc.git
cd dcc-mcp-ipc
poetry installRunning Tasks
nox -s pytest # Run tests
nox -s lint # Lint (mypy + ruff + isort)
nox -s lint-fix # Auto-fix lint issues
nox -s build # Build distribution packagesProject Structure
dcc-mcp-ipc/
├── src/dcc_mcp_ipc/
│ ├── __init__.py # Lazy-import public API surface
│ ├── action_adapter.py # Action system (Rust-backed)
│ ├── adapter/ # DCC & application adapters
│ ├── client/ # Synchronous & async clients + pool
│ ├── server/ # RPyC server + factories + lifecycle
│ ├── transport/ # RPyC / HTTP / WS / IPC transports
│ ├── discovery/ # ZeroConf + file-based service discovery
│ ├── skills/ # SkillManager zero-code system
│ ├── scene/ # Scene operations interface
│ ├── snapshot/ # Snapshot interface
│ ├── application/ # Generic application adapter/service/client
│ ├── testing/ # Mock services for testing
│ └── utils/ # Errors, DI, decorators, RPyC helpers
├── tests/ # 68 test files mirroring source layout
├── examples/ # Usage examples
├── docs/ # VitePress documentation site
└── nox_actions/ # Nox task definitionsLicense
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