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ifly-workflow-mcp-server

MCP.Pizza Chef: iflytek

The ifly-workflow-mcp-server is a lightweight MCP server implementation that integrates iFlytek workflows with the Model Context Protocol. It allows MCP clients and tools to invoke iFlytek's AI-driven workflows seamlessly, enabling rapid development of AI agent platforms and automated workflows. This server acts as a bridge between LLMs and iFlytek's workflow services, facilitating real-time, structured interaction within AI-enhanced applications.

Use This MCP server To

Invoke iFlytek AI workflows from MCP-enabled applications Integrate iFlytek workflow automation into AI agent platforms Enable real-time interaction with iFlytek services via MCP Build custom AI workflows using iFlytek through MCP tools Standardize calls to iFlytek workflows in multi-model environments

README

The fastest way to build workflows with an AI agent platform!

License | Docs | Homepage

iFlytek Workflow MCP Server

The Model Context Protocol (MCP) is an open protocol designed for effortless integration between LLM applications and external data sources or tools, offering a standardized framework to seamlessly provide LLMs with the context they require.

This a simple implementation of an MCP server using iFlytek. It enables calling iFlytek workflows through MCP tools.

Features

Functional Overview

This system is built on the iFlytek MCP server and enables intelligent workflow scheduling, making it suitable for various business scenarios.

  • Workflow Structure: Composed of multiple nodes, supporting 14 types of nodes (including basic, tool, logic, and transformation types).
  • Core Components: By default, the workflow includes a Start Node (user input) and an End Node (output result).
  • Execution Mode: Once triggered, the workflow executes automatically according to predefined sequences and rules, requiring no manual intervention.

Core Capabilities

Robust Node Support
  • 14 types of workflow nodes to meet diverse business requirements.
  • Supports complex variable I/O, enabling flexible data transmission.
Advanced Orchestration Modes
  • Sequential Execution: Tasks execute one after another in order.
  • Parallel Execution: Multiple tasks run simultaneously to enhance efficiency.
  • Loop Execution: Supports iterative loops for handling repetitive tasks.
  • Nested Execution: Allows embedding sub-workflows within workflows, improving reusability.
  • Utilizes the Hook Mechanism to enable streaming output, ensuring real-time processing.
Multiple Development Paradigms
  • Single-turn, single-branch: Linear execution of simple tasks.
  • Single-turn, multi-branch: Supports branching logic to handle complex processes.
  • Single-turn loop: Manages looped tasks to enhance automation.
  • Multi-turn interaction: Supports context memory for dynamic conversations.

Capability Expansion

  • Multi-Model Support: Based on the Model of Models (MoM) hybrid application architecture, providing multiple model choices at critical workflow stages. This allows for flexible model combinations, improving task adaptability.

Usage with MCP client

Prepare config.yaml

Before using the mcp server, you should prepare a config.yaml to save your workflow info. The example config like this:

- flow_id: 'flow id'              # required
  name: 'flow name'               # optional, if not set, obtain the name from the cloud.
  description: 'flow description' # optional, if not set, obtain the description from the cloud.
  api_key: 'API Key:API Secret'   # required
Get workflow authentication information
  1. Create a bot

  2. Publish a workflow

  • Step 1. Debug the workflow you just created.
  • Step 2. Engage in a conversation with your workflow and ensure the conversation is successful.
  • Step 3. You can now click the publish button.
  • Step 4. Select "Publish as API" and click the "Configure" button.
  • Step 5. Select the application you need to bind and bind it. Now you can retrieve the corresponding workflow ID and authentication information. Enjoy!

Note: If you find that you are unable to select an app, you can go to https://www.xfyun.cn to apply.

Manual Installation

To add a persistent client, add the following to your claude_desktop_config.json or mcp.json file:

{
    "mcpServers": {
        "ifly-workflow-mcp-server": {
            "command": "uvx",
            "args": [
                "--from",
                "git+https://github.com/iflytek/ifly-workflow-mcp-server",
                "ifly_workflow_mcp_server"
            ],
            "env": {
                "CONFIG_PATH": "$CONFIG_PATH"
            }
        }
    }
}

Example config:

{
    "mcpServers": {
        "ifly-workflow-mcp-server": {
            "command": "uvx",
            "args": [
                "--from",
                "git+https://github.com/iflytek/ifly-workflow-mcp-server",
                "ifly_workflow_mcp_server"
            ],
            "env": {
                "CONFIG_PATH": "/Users/hygao1024/Projects/config.yaml"
            }
        }
    }
}

ifly-workflow-mcp-server FAQ

How do I set up the ifly-workflow-mcp-server?
Clone the GitHub repo, follow the MIT-licensed documentation, and configure your iFlytek credentials to start calling workflows.
Can this server be used with multiple LLM providers?
Yes, it supports integration with OpenAI, Claude, Gemini, and other MCP-compatible LLMs.
What kind of workflows can I call through this MCP server?
You can invoke any iFlytek workflow available in your account, including AI agent tasks and automation flows.
Is the ifly-workflow-mcp-server secure?
It follows MCP principles for scoped and secure model interaction, but you should also secure your API keys and network access.
Does this server support real-time workflow execution?
Yes, it enables real-time calls to iFlytek workflows from MCP clients and tools.
Where can I find documentation and support?
Documentation and support links are available on the GitHub repo and the iFlytek botcenter homepage.
Can I extend this server to support custom workflows?
Yes, the server is designed to be extensible for custom iFlytek workflow integrations.
What license governs the use of this MCP server?
The server is MIT licensed, allowing flexible use and modification.