MCP Client는 컴퓨터 사용 에이전트(UI-TARS-SDK)를 지원하는 에이전트 전략 플러그인으로 제공됩니다.

[! 중요] Dify는 MCP Server가 아니라 MCP Host입니다.

작동 방식

각 MCP client (ReAct Agent) 노드는 MCP servers를 연결할 수 있습니다.

1. Tool, Resource, Prompt 목록은 Dify 도구로 변환됩니다.
2. 선택한 LLM은 name, description, argument type를 볼 수 있습니다.
3. LLM은 ReAct 루프(관찰 →→ 이유 Reason)를 기반으로 도구를 호출합니다.

[! 참고] 이 저장소의 대부분의 코드는 다음과 같은 파일들을 포함하고 있습니다.

Dify 공식 플러그인 / 에이전트 전략

https://github.com/langgenius/dify-official-plugins/tree/main/agent-strategies/cot_agent

✅ 내가 한 일

• ReAct.py를 복사하고 파일 이름을 [[T13]로 변경)
• mcpReAct.yaml와 [class mcpReActParams()를 편집하여 config_json GUI 입력 필드를 추가했습니다.

mcpReAct.py 에 덧붙였어

• MCP용 새로운 12개 기능
• __init__() AsyncExitStack 및 event loop 초기화를 위한
• _handle_invoke_action()의 MCP용 일부 코드
• [[T21]에서 MCP 설정 및 정리

[! 중요] ReAct while 루프는 현재 상태와 같습니다

🔄 업데이트 기록

• SSE MCP 클라이언트 (v0.0.2) 추가
• 다중 SSE 서버 지원 (v0.0.3)

dify-mcp-client

MCP Client as Agent Strategy Plugin with Computer Using Agent (UI-TARS-SDK) support.

[!IMPORTANT] Dify is not MCP Server but MCP Host.

How it works

Each MCP client (ReAct Agent) node can connect MCP servers.

1. Tool, Resource, Prompt lists are converted into Dify Tools.
2. Your selected LLM can see their name, description, argument type
3. The LLM calls Tools based on the ReAct loop (Reason → Act → Observe).

[!NOTE] Most of the code in this repository contains the following files.

Dify Official Plugins / Agent Strategies

https://github.com/langgenius/dify-official-plugins/tree/main/agent-strategies/cot_agent

✅ What I did

• Copied ReAct.py and renamed file as mcpReAct.py
• Added config_json GUI input field by editing mcpReAct.yaml and class mcpReActParams()

in mcpReAct.py, I added

• New 12 functions for MCP
• __init__() for initializing AsyncExitStack and event loop
• Some codes in _handle_invoke_action() for MCP
• MCP setup and cleanup in _invoke()

[!IMPORTANT] ReAct while loop is as they are

🔄 Update history

• Add SSE MCP client (v0.0.2)
• Support multi SSE servers (v0.0.3)
• Update python module and simplify its dependency (v0.0.4)
  • mcp(v1.1.2→v1.6.0+)
  • dify_plugin(0.0.1b72→v0.1.0)
• Add UI-TARS SDK integration for GUI automation capabilities (v0.0.5)
• Support Streamable HTTP MCP client
• Feat SSE param: /sse?key=value (v0.0.6)

🤖 UI-TARS Integration

This plugin includes UI-TARS SDK integration for GUI automation capabilities.

[!WARNING] UI-TARS-SDK integration is supported only Dify Plugin’s local debug deployment. https://github.com/3dify-project/dify-mcp-client#-how-to-develop-and-deploy-plugin

Normal difypkg install doesn’t work. Because UI-TARS require OS native API, yet Dify plugin env is Linux docker container.

I’m thinking alternative solusion via Streamable HTTP MCP.

Key Features

• On-demand GUI automation: UI-TARS is called only when needed, reducing token consumption
• Life-time control: Set maximum loop count per task to prevent runaway automation

Known Limitations

• Single Monitor Support: UI-TARS currently recognizes the primary monitor only. Multi-monitor setups are not supported.
• Mac Retina Display Issue: On macOS with Retina displays, UI-TARS requires the display resolution to be set to “Default” instead of the highest quality setting. Otherwise wrong (w,h) point is clicked. https://github.com/bytedance/UI-TARS-desktop/issues/591

Life-time Parameter

The life_time parameter controls the maximum number of GUI actions UI-TARS can perform:

• Default: 10 iterations
• User-configurable maximum via ui_tars_max_life_time_count
• Your selected LLM can dynamically adjust within the user-defined limit based on task complexity

[!NOTE]