iFlytek Workflow MCP Server

What does “iFlytek Workflow” MCP Server do?

The iFlytek Workflow MCP Server is a simple implementation of the Model Context Protocol (MCP) that enables seamless integration between AI assistants and iFlytek’s workflow automation platform. Acting as a bridge, it allows AI agents to schedule and execute sophisticated workflows composed of multiple node types (basic, tool, logic, transformation) through MCP tools. This facilitates intelligent workflow orchestration, data processing, and automation tasks, enhancing development workflows. With support for diverse orchestration modes like sequential, parallel, loop, and nested execution, the server is particularly well-suited for business automation, dynamic conversational flows, and integrating multiple AI models into complex pipelines. It enables developers to trigger, manage, and monitor workflows programmatically with minimal manual intervention.

List of Prompts

No prompt templates are explicitly mentioned in the repository or documentation.

List of Resources

No explicit resources are documented or defined in the repository or documentation.

List of Tools

• The main tool exposed is the ability to call iFlytek workflows through MCP tools. This enables the triggering and execution of predefined workflows based on provided workflow information such as the flow ID.

Use Cases of this MCP Server

• Business Workflow Automation: Automate multi-step business processes by triggering iFlytek workflows that can handle sequential, parallel, and conditional logic, reducing manual effort and errors.
• AI-Driven Data Processing: Enable AI agents to manage complex data transformation and processing tasks by orchestrating various workflow nodes, supporting variable I/O and streaming outputs.
• Conversational AI with Context Memory: Implement multi-turn, context-aware conversations in AI assistants by leveraging workflows that support context memory and dynamic branching.
• Hybrid Model Orchestration: Combine and switch between different AI models at critical workflow stages using the Model of Models (MoM) architecture, optimizing task performance.
• Real-Time Monitoring and Feedback: Use streaming output hooks to provide real-time updates and results to end-users or other systems during workflow execution.

How to set it up

Windsurf

1. Ensure that you have Node.js installed as a prerequisite.
2. Open the Windsurf configuration file (usually windsurf.config.json).
3. Add the iFlytek Workflow MCP Server using the following JSON snippet:

   {
     "mcpServers": {
       "iflytek-workflow-mcp": {
         "command": "npx",
         "args": ["@iflytek/ifly-workflow-mcp-server@latest"]
       }
     }
   }
   

4. Save the configuration file and restart Windsurf.
5. Verify the setup by checking if the MCP server is running and accessible.

Securing API Keys

Use environment variables for sensitive data:

{
  "mcpServers": {
    "iflytek-workflow-mcp": {
      "command": "npx",
      "args": ["@iflytek/ifly-workflow-mcp-server@latest"],
      "env": {
        "XFYUN_API_KEY": "${XFYUN_API_KEY}"
      },
      "inputs": {
        "flow_id": "your_flow_id"
      }
    }
  }
}

Claude

1. Install Node.js if not already installed.
2. Locate Claude’s MCP configuration file.
3. Add the iFlytek Workflow MCP Server entry as shown:

   {
     "mcpServers": {
       "iflytek-workflow-mcp": {
         "command": "npx",
         "args": ["@iflytek/ifly-workflow-mcp-server@latest"]
       }
     }
   }
   

4. Save the file and restart Claude.
5. Confirm the server is operational.

Securing API Keys

Use environment variables in the configuration as above.

Cursor

1. Install Node.js if required.
2. Edit Cursor’s configuration file to include the MCP server:

   {
     "mcpServers": {
       "iflytek-workflow-mcp": {
         "command": "npx",
         "args": ["@iflytek/ifly-workflow-mcp-server@latest"]
       }
     }
   }
   

3. Save changes and restart Cursor.
4. Ensure connectivity to the MCP server.

Securing API Keys

Use the env and inputs fields as shown in previous examples.

Cline

1. Ensure Node.js is installed.
2. Open Cline’s configuration file.
3. Add the following MCP server configuration:

   {
     "mcpServers": {
       "iflytek-workflow-mcp": {
         "command": "npx",
         "args": ["@iflytek/ifly-workflow-mcp-server@latest"]
       }
     }
   }
   

4. Save and restart Cline.
5. Check for successful startup.

Securing API Keys

Follow the same environment variable pattern for sensitive configuration.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "iflytek-workflow-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “iflytek-workflow-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

| Supports Roots | ⛔ | No mention of Roots support found. | | Supports Sampling | ⛔ | No mention of Sampling support found. |

Based on the above tables, the iFlytek Workflow MCP Server offers basic MCP server functionality with workflow execution capabilities but lacks advanced MCP features like prompt templates, resource definitions, roots, and sampling. Its documentation is focused on setup and business workflow utility but does not provide deep technical integration details.

Our opinion

Given the focus on workflow execution and automation but the absence of deeper MCP features like roots, sampling, and resource/prompt templates, we would rate this MCP server as a 4/10 for overall MCP ecosystem completeness. It is functional for its niche use case but limited for broader or more advanced MCP integrations.

MCP Score