diff --git a/__init__.py b/__init__.py
index b393a96..b8f3cd2 100644
--- a/__init__.py
+++ b/__init__.py
@@ -1,4 +1,4 @@
-from . import api, nodes, tile, region, nsfw, translation
+from . import api, nodes, tile, region, nsfw, translation, krita
 
 NODE_CLASS_MAPPINGS = {
     "ETN_LoadImageBase64": nodes.LoadImageBase64,
@@ -17,6 +17,12 @@ NODE_CLASS_MAPPINGS = {
     "ETN_AttentionMask": region.AttentionMask,
     "ETN_NSFWFilter": nsfw.NSFWFilter,
     "ETN_Translate": translation.Translate,
+    "ETN_KritaOutput": krita.KritaOutput,
+    "ETN_KritaCanvas": krita.KritaCanvas,
+    "ETN_KritaSelection": krita.KritaSelection,
+    "ETN_KritaImageLayer": krita.KritaImageLayer,
+    "ETN_KritaMaskLayer": krita.KritaMaskLayer,
+    "ETN_IntParameter": krita.IntParameter,
 }
 NODE_DISPLAY_NAME_MAPPINGS = {
     "ETN_LoadImageBase64": "Load Image (Base64)",
@@ -35,5 +41,11 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ETN_AttentionMask": "Regions Attention Mask",
     "ETN_NSFWFilter": "NSFW Filter",
     "ETN_Translate": "Translate Text",
+    "ETN_KritaOutput": "Krita Output",
+    "ETN_KritaCanvas": "Krita Canvas",
+    "ETN_KritaSelection": "Krita Selection",
+    "ETN_KritaImageLayer": "Krita Image Layer",
+    "ETN_KritaMaskLayer": "Krita Mask Layer",
+    "ETN_IntParameter": "Integer Parameter",
 }
 WEB_DIRECTORY = "./js"
diff --git a/api.py b/api.py
index e7a3d3f..2de09cc 100644
--- a/api.py
+++ b/api.py
@@ -13,6 +13,7 @@ import folder_paths
 import server
 
 from .translation import available_languages, translate
+from .krita import WorkflowExchange
 
 input_block_name = "model.diffusion_model.input_blocks.0.0.weight"
 
@@ -127,41 +128,6 @@ def has_invalid_filename(filename: str):
     return None
 
 
-class Publisher(NamedTuple):
-    name: str
-    id: str
-    workflow: dict
-
-
-class WorkflowExchange:
-    def __init__(self, server: server.PromptServer):
-        self._server = server
-        self._publishers: dict[str, Publisher] = {}
-        self._subscribers: list[str] = []
-
-    async def publish(self, publisher_name: str, publisher_id: str, workflow: dict):
-        name = f"{publisher_name} ({publisher_id})"
-        publisher = Publisher(name, publisher_id, workflow)
-        for client_id in self._subscribers:
-            await self._notify(client_id, publisher)
-        self._publishers[publisher_id] = publisher
-        print(f"Published workflow from {name}: {workflow}")
-
-    async def subscribe(self, client_id: str):
-        if client_id in self._subscribers:
-            raise KeyError("Already subscribed")
-        self._subscribers.append(client_id)
-        for publisher in self._publishers.values():
-            await self._notify(client_id, publisher)
-
-    def unsubscribe(self, client_id: str):
-        self._subscribers.remove(client_id)
-
-    async def _notify(self, client_id: str, publisher: Publisher):
-        data = {"publisher": publisher.name, "workflow": publisher.workflow}
-        await self._server.send_json("etn_workflow_changed", data, client_id)
-
-
 _server: server.PromptServer | None = getattr(server.PromptServer, "instance", None)
 if _server is not None:
 
diff --git a/krita.py b/krita.py
new file mode 100644
index 0000000..6c30987
--- /dev/null
+++ b/krita.py
@@ -0,0 +1,137 @@
+import torch
+from typing import NamedTuple
+
+import server
+from .nodes import SendImageWebSocket
+
+
+class Publisher(NamedTuple):
+    name: str
+    id: str
+    workflow: dict
+
+
+class WorkflowExchange:
+    def __init__(self, server: server.PromptServer):
+        self._server = server
+        self._publishers: dict[str, Publisher] = {}
+        self._subscribers: list[str] = []
+
+    async def publish(self, publisher_name: str, publisher_id: str, workflow: dict):
+        publisher = Publisher(publisher_name, publisher_id, workflow)
+        for client_id in self._subscribers:
+            await self._notify(client_id, publisher)
+        self._publishers[publisher_id] = publisher
+
+    async def subscribe(self, client_id: str):
+        if client_id in self._subscribers:
+            raise KeyError("Already subscribed")
+        self._subscribers.append(client_id)
+        for publisher in self._publishers.values():
+            await self._notify(client_id, publisher)
+
+    def unsubscribe(self, client_id: str):
+        self._subscribers.remove(client_id)
+
+    async def _notify(self, client_id: str, publisher: Publisher):
+        data = {
+            "publisher": {"name": publisher.name, "id": publisher.id},
+            "workflow": publisher.workflow,
+        }
+        await self._server.send_json("etn_workflow_published", data, client_id)
+
+
+class KritaOutput(SendImageWebSocket):
+    RETURN_TYPES = ()
+    FUNCTION = "send_images"
+    OUTPUT_NODE = True
+    CATEGORY = "krita"
+
+
+class KritaCanvas:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {}
+
+    RETURN_TYPES = ("IMAGE", "INT", "INT", "INT")
+    RETURN_NAMES = ("image", "width", "height", "seed")
+    FUNCTION = "placeholder"
+    CATEGORY = "krita"
+
+    def placeholder(self):
+        empty = torch.zeroes(1, 512, 512, 3)
+        return (empty, 512, 512, 0)
+
+
+class KritaSelection:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {}
+
+    RETURN_TYPES = ("MASK",)
+    RETURN_NAMES = ("mask",)
+    FUNCTION = "placeholder"
+    CATEGORY = "krita"
+
+    def placeholder(self):
+        empty = torch.ones(1, 512, 512)
+        return (empty,)
+
+
+class KritaImageLayer:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "name": ("STRING", {"default": "Image"}),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "placeholder"
+    CATEGORY = "krita"
+
+    def placeholder(self, name: str):
+        empty = torch.zeros(1, 512, 512, 3)
+        return (empty,)
+
+
+class KritaMaskLayer:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "name": ("STRING", {"default": "Mask"}),
+            }
+        }
+
+    RETURN_TYPES = ("MASK",)
+    RETURN_NAMES = ("mask",)
+    FUNCTION = "placeholder"
+    CATEGORY = "krita"
+
+    def placeholder(self, name: str):
+        empty = torch.ones(1, 512, 512)
+        return (empty,)
+
+
+class IntParameter:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "name": ("STRING", {"default": "Parameter"}),
+                "min": ("INT", {"default": 0}),
+                "max": ("INT", {"default": 100}),
+                "default": ("INT", {"default": 50}),
+            }
+        }
+
+    RETURN_TYPES = ("INT",)
+    RETURN_NAMES = ("value",)
+    FUNCTION = "placeholder"
+    CATEGORY = "krita"
+
+    def placeholder(self, name: str, min: int, max: int, default: int):
+        return (default,)