dify-mcp-client

by 3dify-project

169 stars

758 downloads

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GitHub

Developer Tools

About

MCP Client as an Agent Strategy Plugin. Support GUI operation via UI-TARS-SDK.

Details

Author: 3dify-project
GitHub stars: 169
Downloads: 758
Categories: Developer Tools

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name dify-mcp-client

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

From the repository

Install the plugin from GitHub or from a .difypkg release file via Dify's plugin manager. After installation, add an Agent node in any Dify Chatflow and select "mcpReAct" as the agent strategy. Configure the config_json field with server URLs (SSE or Streamable HTTP) to connect MCP servers.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "dify-mcp-client": {
            "dify-mcp-client": {
                "command": "docker",
                "args": [
                    "build",
                    "-t",
                    "dify-mcp-client:latest",
                    "."
                ]
            }
        }
    }
}

McpServers

{
    "dify-mcp-client": {
        "command": "docker",
        "args": [
            "build",
            "-t",
            "dify-mcp-client:latest",
            "."
        ]
    }
}

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.

showcase1

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]
> Currently hardcoded to use UI-TARS-1.5-7B model for optimal cost-performance balance.

🐳 Docker Deployment with Pre-built Node.js

Building the Docker Image

<details> <summary> This pulldown guide is for TypeScript stdio MCP server user</summary>

docker build -t dify-mcp-client:latest .

Or use our pre-built image:
```yaml

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About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

dify-mcp-client

How it works

✅ What I did

in mcpReAct.py, I added

🔄 Update history

🤖 UI-TARS Integration

Key Features

Known Limitations

Life-time Parameter

🐳 Docker Deployment with Pre-built Node.js

Building the Docker Image

Install

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