diff --git a/agent-tools/mcp.mdx b/agent-tools/mcp.mdx
index 7bc8e4c9c..118164b73 100644
--- a/agent-tools/mcp.mdx
+++ b/agent-tools/mcp.mdx
@@ -1,7 +1,7 @@
 ---
-title: "Comfy MCP"
+title: "Comfy MCP: Connect AI Agents to ComfyUI"
 sidebarTitle: "Comfy MCP"
-description: "Connect any AI agent to ComfyUI on Comfy Cloud GPUs or on your own machine. Generate images, video, audio and 3D, search models, nodes and templates, and run real workflows."
+description: "Connect AI agents to ComfyUI over the Model Context Protocol. Generate images, video, audio, and 3D, and run real workflows on Comfy Cloud or your own machine."
 icon: "bolt"
 ---
 
diff --git a/custom-nodes/backend/datatypes.mdx b/custom-nodes/backend/datatypes.mdx
index c72010c4b..029a87317 100644
--- a/custom-nodes/backend/datatypes.mdx
+++ b/custom-nodes/backend/datatypes.mdx
@@ -1,6 +1,6 @@
 ---
-title: "Datatypes"
-description: "Comprehensive reference for ComfyUI custom node data types. Learn how to define Python types, tensor formats (IMAGE, LATENT, MASK), custom data types, and wildcards in INPUT_TYPES."
+title: "ComfyUI Custom Node Datatypes"
+description: "Reference for ComfyUI custom node data types: Python types, tensor formats (IMAGE, LATENT, MASK), custom types, and wildcards in INPUT_TYPES."
 ---
 
 These are the most important built in datatypes. You can also [define your own]( ./more_on_inputs#custom-datatypes).
diff --git a/ja/agent-tools/mcp.mdx b/ja/agent-tools/mcp.mdx
index 602fd1c3f..2c9e9b833 100644
--- a/ja/agent-tools/mcp.mdx
+++ b/ja/agent-tools/mcp.mdx
@@ -1,15 +1,15 @@
 ---
-title: "Comfy MCP"
+title: "Comfy MCP：AIエージェントをComfyUIに接続"
 sidebarTitle: "Comfy MCP"
-description: "あらゆる AI エージェントを Comfy Cloud GPU 上、または自分のマシン上の ComfyUI に接続します。画像、動画、音声、3D を生成し、モデル、ノード、テンプレートを検索し、実際のワークフローを実行できます。"
+description: "Model Context Protocol（MCP）で AI エージェントを ComfyUI に接続。画像、動画、音声、3D を生成し、Comfy Cloud または自分のマシンで実際のワークフローを実行できます。"
 icon: "bolt"
-translationSourceHash: e39d4681
+translationSourceHash: 26d1bc72
 translationFrom: agent-tools/mcp.mdx
 translationBlockHashes:
   "_intro": 340316c1
   "Overview": 64064e0e
   "Comfy Cloud MCP Connection": f820ca16
-  "Local Comfy MCP Connection": 5b13e8fd
+  "Local Comfy MCP Connection": 59170570
   "Related resources": 2a86e2c5
   "Related: Comfy In-App Agent": be5e2cdf
   "Feedback": 25a3d53f
diff --git a/ja/custom-nodes/backend/datatypes.mdx b/ja/custom-nodes/backend/datatypes.mdx
index 1f4995fdf..f55198d8d 100644
--- a/ja/custom-nodes/backend/datatypes.mdx
+++ b/ja/custom-nodes/backend/datatypes.mdx
@@ -1,6 +1,6 @@
 ---
-title: "データ型"
-description: "ComfyUI カスタムノードのデータ型に関する包括的なリファレンス。Python 型の定義、テンソル形式（IMAGE、LATENT、MASK）、カスタムデータ型、INPUT_TYPES のワイルドカードを学べます。"
+title: "ComfyUI カスタムノードのデータ型"
+description: "ComfyUI カスタムノードのデータ型リファレンス：Python 型、テンソル形式（IMAGE、LATENT、MASK）、カスタム型、INPUT_TYPES のワイルドカード。"
 translationSourceHash: f04aba65
 translationFrom: custom-nodes/backend/datatypes.mdx
 translationBlockHashes:
diff --git a/ja/tutorials/image/z-image/z-image.mdx b/ja/tutorials/image/z-image/z-image.mdx
index 36d3b562d..b03803ed3 100644
--- a/ja/tutorials/image/z-image/z-image.mdx
+++ b/ja/tutorials/image/z-image/z-image.mdx
@@ -1,6 +1,6 @@
 ---
 title: "Z-Image ComfyUI ワークフロー例"
-description: "Z-Image は、コミュニティ主導のファインチューニングおよびカスタム開発に適した、6B パラメータの高効率画像生成基盤モデルであり、単一ストリーム拡散トランスフォーマー（Single-Stream Diffusion Transformer）を採用しています。"
+description: "Z-Image は Alibaba Tongyi Lab の 6B 高効率画像生成基盤モデル。単一ストリーム DiT 設計で、ファインチューニングとカスタム開発に最適です。"
 sidebarTitle: "Z-Image"
 translationSourceHash: 613b8f98
 translationFrom: tutorials/image/z-image/z-image.mdx
diff --git a/ja/tutorials/partner-nodes/lightricks/ltx-2-5.mdx b/ja/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
index 08f7fd402..3606beb73 100644
--- a/ja/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
+++ b/ja/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
@@ -1,8 +1,8 @@
 ---
 title: "ComfyUIでのLTX-2.5 APIビデオ生成"
-description: "ComfyUIでLTX-2.5 APIノードをクラウドワークフローとともに使用して、テキストから動画、画像から動画、最初と最後のフレームから動画への生成方法を、FastとProモデルティアを含めて学びます。"
+description: "ComfyUI の LTX-2.5 API ノードで、テキスト、画像、または最初と最後のフレームから動画を生成。Fast と Pro の 2 つのモデルがあり、ローカル GPU は不要です。"
 sidebarTitle: "LTX-2.5 API"
-translationSourceHash: 2cafd208
+translationSourceHash: 71a8eebe
 translationFrom: tutorials/partner-nodes/lightricks/ltx-2-5.mdx
 ---
 
diff --git a/ja/tutorials/video/wan/fun-inp.mdx b/ja/tutorials/video/wan/fun-inp.mdx
index f0dbe9ccc..43570d9e5 100644
--- a/ja/tutorials/video/wan/fun-inp.mdx
+++ b/ja/tutorials/video/wan/fun-inp.mdx
@@ -2,10 +2,10 @@
 title: "ComfyUI Wan2.1 Fun InP 動画サンプル"
 description: "このガイドでは、ComfyUI で Wan2.1 Fun InP を使用して、最初と最後のフレームを制御した動画を生成する方法について説明します"
 sidebarTitle: "Wan2.1 Fun InP"
-translationSourceHash: 142c582d
+translationSourceHash: cc5554a3
 translationFrom: tutorials/video/wan/fun-inp.mdx
 translationBlockHashes:
-  "_intro": 9efc0241
+  "_intro": e1ce7f2d
   "About Wan2.1-Fun-InP": f67d80ee
   "Wan2.1 Fun InP Workflow": 900df71d
   "Other Wan2.1 Fun InP or video-related custom node packages": 4c96c810
@@ -13,6 +13,10 @@ translationBlockHashes:
 
 import UpdateReminder from "/snippets/ja/tutorials/update-reminder.mdx";
 
+**Wan2.1 Fun InP** は、Alibaba の Wan2.1-Fun シリーズに属するオープンソースの動画生成モデルです。最初と最後のフレーム画像を指定すると、その間の遷移動画を生成し、安定した一貫性のある動きを実現します。
+
+このガイドでは、ComfyUI 公式の Wan2.1 Fun InP ワークフローを紹介します。軽量な 1.3B 版と高性能な 14B 版があり、モデルのダウンロードと段階的な生成手順を解説します。
+
 ## Wan2.1-Fun-InP について
 
 **Wan-Fun InP** は、アリババによってリリースされたオープンソースの動画生成モデルで、Wan2.1-Fun シリーズの一部であり、画像から動画を生成し、最初と最後のフレームを制御することに重点を置いています。
diff --git a/ko/agent-tools/mcp.mdx b/ko/agent-tools/mcp.mdx
index 9fce3d134..2c7653a8d 100644
--- a/ko/agent-tools/mcp.mdx
+++ b/ko/agent-tools/mcp.mdx
@@ -1,19 +1,19 @@
 ---
-title: "Comfy MCP"
+title: "Comfy MCP: AI 에이전트를 ComfyUI에 연결"
 sidebarTitle: "Comfy MCP"
-description: "Comfy Cloud GPU 또는 자신의 컴퓨터에서 ComfyUI에 AI 에이전트를 연결하세요. 이미지, 비디오, 오디오, 3D를 생성하고, 모델, 노드, 템플릿을 검색하며, 실제 워크플로를 실행할 수 있습니다."
+description: "Model Context Protocol(MCP)로 AI 에이전트를 ComfyUI에 연결하세요. 이미지, 비디오, 오디오, 3D를 생성하고 Comfy Cloud 또는 자신의 컴퓨터에서 실제 워크플로를 실행할 수 있습니다."
 icon: "bolt"
-translationSourceHash: 397db1ab
+translationSourceHash: 26d1bc72
 translationFrom: agent-tools/mcp.mdx
 translationBlockHashes:
   "_intro": 340316c1
   "Overview": 64064e0e
   "Comfy Cloud MCP Connection": f820ca16
-  "Local Comfy MCP Connection": 8710a546
+  "Local Comfy MCP Connection": 59170570
   "Related resources": 2a86e2c5
   "Related: Comfy In-App Agent": be5e2cdf
   "Feedback": 25a3d53f
-  "FAQ": 45b297ec
+  "FAQ": 5c144ebc
 ---
 
 
diff --git a/ko/custom-nodes/backend/datatypes.mdx b/ko/custom-nodes/backend/datatypes.mdx
index 5c5a1f7b4..2cedf5d37 100644
--- a/ko/custom-nodes/backend/datatypes.mdx
+++ b/ko/custom-nodes/backend/datatypes.mdx
@@ -1,6 +1,6 @@
 ---
-title: "데이터 타입"
-description: "ComfyUI 커스텀 노드 데이터 타입 종합 레퍼런스. Python 타입 정의, 텐서 형식(IMAGE, LATENT, MASK), 커스텀 데이터 타입, INPUT_TYPES의 와일드카드를 배웁니다."
+title: "ComfyUI 커스텀 노드 데이터 타입"
+description: "ComfyUI 커스텀 노드 데이터 타입 레퍼런스: Python 타입, 텐서 형식(IMAGE, LATENT, MASK), 커스텀 타입, INPUT_TYPES의 와일드카드."
 translationSourceHash: f04aba65
 translationFrom: custom-nodes/backend/datatypes.mdx
 translationBlockHashes:
diff --git a/ko/tutorials/image/z-image/z-image.mdx b/ko/tutorials/image/z-image/z-image.mdx
index b6f312156..ebf3748ba 100644
--- a/ko/tutorials/image/z-image/z-image.mdx
+++ b/ko/tutorials/image/z-image/z-image.mdx
@@ -1,12 +1,12 @@
 ---
 title: "Z-Image ComfyUI 워크플로우 예시"
-description: "Z-Image는 6B 파라미터를 갖춘 효율적인 이미지 생성 기반 모델로, 단일 스트림 확산 트랜스포머를 사용해 커뮤니티 주도의 미세조정 및 맞춤형 개발이 가능합니다."
+description: "Z-Image는 알리바바 통이 연구소의 6B 효율적 이미지 생성 기반 모델로, 단일 스트림 DiT 설계로 미세조정 및 맞춤형 개발에 적합합니다."
 sidebarTitle: "Z-Image"
-translationSourceHash: 5c356d79
+translationSourceHash: 613b8f98
 translationFrom: tutorials/image/z-image/z-image.mdx
 translationBlockHashes:
   "_intro": e00a79e0
-  "Z-Image text-to-image workflow": f291cf11
+  "Z-Image text-to-image workflow": 49b8d4a9
   "Z-Image model downloads": 02a933e1
 ---
 
diff --git a/ko/tutorials/partner-nodes/lightricks/ltx-2-5.mdx b/ko/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
index 911aef915..f28f981d7 100644
--- a/ko/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
+++ b/ko/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
@@ -1,8 +1,8 @@
 ---
 title: "ComfyUI에서 LTX-2.5 API 비디오 생성"
-description: "클라우드 워크플로에서 텍스트 기반 비디오 생성, 이미지 기반 비디오 생성, 첫 번째 및 마지막 프레임 기반 비디오 생성을 위한 LTX-2.5 API 노드 사용법과 Fast 및 Pro 모델 등급에 대해 알아보세요."
+description: "ComfyUI에서 LTX-2.5 API 노드를 사용해 텍스트, 이미지 또는 첫·마지막 프레임으로 동영상을 생성하세요. Fast 및 Pro 등급을 제공하며 로컬 GPU가 필요 없습니다."
 sidebarTitle: "LTX-2.5 API"
-translationSourceHash: 2cafd208
+translationSourceHash: 71a8eebe
 translationFrom: tutorials/partner-nodes/lightricks/ltx-2-5.mdx
 ---
 
diff --git a/ko/tutorials/video/wan/fun-inp.mdx b/ko/tutorials/video/wan/fun-inp.mdx
index 052ddc204..2cf073a24 100644
--- a/ko/tutorials/video/wan/fun-inp.mdx
+++ b/ko/tutorials/video/wan/fun-inp.mdx
@@ -2,10 +2,10 @@
 title: "ComfyUI Wan2.1 Fun InP 동영상 예시"
 description: "이 가이드에서는 ComfyUI에서 Wan2.1 Fun InP를 사용해 첫 프레임과 마지막 프레임 제어 기능을 갖춘 동영상을 생성하는 방법을 보여줍니다."
 sidebarTitle: "Wan2.1 Fun InP"
-translationSourceHash: 142c582d
+translationSourceHash: cc5554a3
 translationFrom: tutorials/video/wan/fun-inp.mdx
 translationBlockHashes:
-  "_intro": 9efc0241
+  "_intro": e1ce7f2d
   "About Wan2.1-Fun-InP": f67d80ee
   "Wan2.1 Fun InP Workflow": 900df71d
   "Other Wan2.1 Fun InP or video-related custom node packages": 4c96c810
@@ -14,6 +14,10 @@ translationBlockHashes:
 
 import UpdateReminder from "/snippets/ko/tutorials/update-reminder.mdx";
 
+**Wan2.1 Fun InP**는 알리바바 Wan2.1-Fun 시리즈의 오픈소스 동영상 생성 모델입니다. 첫 프레임과 마지막 프레임 이미지를 지정하면 그 사이의 전환 동영상을 생성하여 안정적이고 일관된 움직임을 만들어냅니다.
+
+이 가이드는 ComfyUI 공식 Wan2.1 Fun InP 워크플로우를 소개합니다. 가벼운 1.3B 버전과 고성능 14B 버전으로 제공되며, 모델 다운로드와 단계별 생성 방법을 다룹니다.
+
 ## Wan2.1-Fun-InP 소개
 
 **Wan-Fun InP**는 알리바바가 공개한 오픈소스 영상 생성 모델로, Wan2.1-Fun 시리즈의 일부이며, 이미지로부터 첫 프레임과 마지막 프레임 제어 기능을 갖춘 동영상을 생성하는 데 중점을 두고 있습니다.
diff --git a/tutorials/image/z-image/z-image.mdx b/tutorials/image/z-image/z-image.mdx
index 5b182393b..49aedfe1e 100644
--- a/tutorials/image/z-image/z-image.mdx
+++ b/tutorials/image/z-image/z-image.mdx
@@ -1,6 +1,6 @@
 ---
 title: "Z-Image ComfyUI Workflow Example"
-description: "Z-Image is a 6B parameter efficient image generation foundation model with single-stream diffusion transformer for community-driven fine-tuning and custom development."
+description: "Z-Image is a 6B efficient image generation foundation model from Alibaba Tongyi Lab. Its single-stream DiT design targets fine-tuning and custom development."
 sidebarTitle: "Z-Image"
 ---
 
diff --git a/tutorials/partner-nodes/lightricks/ltx-2-5.mdx b/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
index 75c8c2743..b05073dda 100644
--- a/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
+++ b/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
@@ -1,6 +1,6 @@
 ---
 title: "LTX-2.5 API Video Generation in ComfyUI"
-description: "Learn how to use the LTX-2.5 API nodes in ComfyUI with cloud workflows for text-to-video, image-to-video, and first-last-frame-to-video, with Fast and Pro model tiers."
+description: "Use LTX-2.5 API nodes in ComfyUI to generate video from text, images, or first and last frames, with Fast and Pro tiers. No local GPU required."
 sidebarTitle: "LTX-2.5 API"
 ---
 
diff --git a/tutorials/video/wan/fun-inp.mdx b/tutorials/video/wan/fun-inp.mdx
index f0a1b6cb4..e919aeafa 100644
--- a/tutorials/video/wan/fun-inp.mdx
+++ b/tutorials/video/wan/fun-inp.mdx
@@ -6,6 +6,10 @@ sidebarTitle: "Wan2.1 Fun InP"
 
 import UpdateReminder from "/snippets/tutorials/update-reminder.mdx";
 
+**Wan2.1 Fun InP** is an open-source video generation model in Alibaba's Wan2.1-Fun series. You provide a first and last frame image, and it generates the transition video between them with stable, coherent motion.
+
+This guide covers the official ComfyUI workflow for Wan2.1 Fun InP, available in lightweight 1.3B and high-performance 14B versions, with model downloads and step-by-step generation instructions.
+
 ## About Wan2.1-Fun-InP
 
 **Wan-Fun InP** is an open-source video generation model released by Alibaba, part of the Wan2.1-Fun series, focusing on generating videos from images with first and last frame control.
diff --git a/zh/agent-tools/mcp.mdx b/zh/agent-tools/mcp.mdx
index eedf5b7f1..3ac2db5d0 100644
--- a/zh/agent-tools/mcp.mdx
+++ b/zh/agent-tools/mcp.mdx
@@ -1,15 +1,15 @@
 ---
-title: "Comfy MCP"
+title: "Comfy MCP：将 AI 智能体连接到 ComfyUI"
 sidebarTitle: "Comfy MCP"
-description: "将任意 AI 智能体连接到 Comfy Cloud GPU 或本机上的 ComfyUI。生成图像、视频、音频和 3D，搜索模型、节点与模板，并运行真实工作流。"
+description: "通过模型上下文协议（MCP）将 AI 智能体连接到 ComfyUI。可生成图像、视频、音频和 3D，并在 Comfy Cloud 或本机运行真实工作流。"
 icon: "bolt"
-translationSourceHash: 2d83b9f2
+translationSourceHash: 26d1bc72
 translationFrom: agent-tools/mcp.mdx
 translationBlockHashes:
   "_intro": 340316c1
   "Overview": 64064e0e
   "Comfy Cloud MCP Connection": f820ca16
-  "Local Comfy MCP Connection": 8710a546
+  "Local Comfy MCP Connection": 59170570
   "Related resources": 2a86e2c5
   "Related: Comfy In-App Agent": be5e2cdf
   "Feedback": 25a3d53f
diff --git a/zh/custom-nodes/backend/datatypes.mdx b/zh/custom-nodes/backend/datatypes.mdx
index f26f54873..8dad84829 100644
--- a/zh/custom-nodes/backend/datatypes.mdx
+++ b/zh/custom-nodes/backend/datatypes.mdx
@@ -1,6 +1,6 @@
 ---
-title: "数据类型"
-description: "ComfyUI 自定义节点数据类型完整参考。学习如何定义 Python 类型、张量格式（IMAGE、LATENT、MASK）、自定义数据类型，以及 INPUT_TYPES 中的通配符。"
+title: "ComfyUI 自定义节点数据类型"
+description: "ComfyUI 自定义节点数据类型参考：Python 类型、张量格式（IMAGE、LATENT、MASK）、自定义类型，以及 INPUT_TYPES 中的通配符。"
 translationSourceHash: f04aba65
 translationFrom: custom-nodes/backend/datatypes.mdx
 translationBlockHashes:
diff --git a/zh/tutorials/image/z-image/z-image.mdx b/zh/tutorials/image/z-image/z-image.mdx
index 4a2536372..483324852 100644
--- a/zh/tutorials/image/z-image/z-image.mdx
+++ b/zh/tutorials/image/z-image/z-image.mdx
@@ -1,6 +1,6 @@
 ---
 title: "Z-Image ComfyUI 工作流示例"
-description: "Z-Image 是一个拥有 6B 参数的高效图像生成基础模型，采用单流扩散变换器架构，适用于社区驱动的微调和自定义开发。"
+description: "Z-Image 是阿里通义实验室推出的 6B 高效图像生成基础模型，采用单流 DiT 架构，适合微调和自定义开发。"
 sidebarTitle: "Z-Image"
 translationSourceHash: 613b8f98
 translationFrom: tutorials/image/z-image/z-image.mdx
diff --git a/zh/tutorials/partner-nodes/lightricks/ltx-2-5.mdx b/zh/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
index 210a942cc..e621aabff 100644
--- a/zh/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
+++ b/zh/tutorials/partner-nodes/lightricks/ltx-2-5.mdx
@@ -1,8 +1,8 @@
 ---
 title: "在 ComfyUI 中使用 LTX-2.5 API 生成视频"
-description: "了解如何结合云端工作流，在 ComfyUI 中使用 LTX-2.5 API 节点进行文生视频、图生视频和首尾帧生视频，并提供 Fast 与 Pro 两种模型档位。"
+description: "在 ComfyUI 中使用 LTX-2.5 API 节点，通过文生视频、图生视频和首尾帧生视频工作流生成视频，提供 Fast 与 Pro 档位，无需本地 GPU。"
 sidebarTitle: "LTX-2.5 API"
-translationSourceHash: 2cafd208
+translationSourceHash: 71a8eebe
 translationFrom: tutorials/partner-nodes/lightricks/ltx-2-5.mdx
 ---
 
diff --git a/zh/tutorials/video/wan/fun-inp.mdx b/zh/tutorials/video/wan/fun-inp.mdx
index 65da89b4e..3227e76c0 100644
--- a/zh/tutorials/video/wan/fun-inp.mdx
+++ b/zh/tutorials/video/wan/fun-inp.mdx
@@ -2,10 +2,10 @@
 title: "ComfyUI Wan2.1 Fun InP 视频示例"
 description: "本文介绍了如何在 ComfyUI 中完成 Wan2.1 Fun InP 视频首尾帧视频生成示例"
 sidebarTitle: "Wan2.1 Fun InP"
-translationSourceHash: 142c582d
+translationSourceHash: cc5554a3
 translationFrom: tutorials/video/wan/fun-inp.mdx
 translationBlockHashes:
-  "_intro": 9efc0241
+  "_intro": e1ce7f2d
   "About Wan2.1-Fun-InP": f67d80ee
   "Wan2.1 Fun InP Workflow": 900df71d
   "Other Wan2.1 Fun InP or video-related custom node packages": 4c96c810
@@ -14,6 +14,10 @@ translationBlockHashes:
 
 import UpdateReminder from '/snippets/zh/tutorials/update-reminder.mdx'
 
+**Wan2.1 Fun InP** 是阿里 Wan2.1-Fun 系列的开源视频生成模型。你提供首帧和尾帧图像，它便生成两者之间的过渡视频，画面稳定且运动连贯。
+
+本指南介绍 ComfyUI 官方的 Wan2.1 Fun InP 工作流，提供轻量的 1.3B 和高性能的 14B 两个版本，涵盖模型下载和分步生成教程。
+
 ## 关于 Wan2.1-Fun-InP
 
 **Wan-Fun InP** 是阿里巴巴推出的开源视频生成模型，属于 Wan2.1-Fun 系列的一部分，专注于通过图像生成视频并实现首尾帧控制。