iflow-mcp_iflytek_ifly-workflow-mcp-server 1.0.0
This a simple implementation of an MCP server using iFlytek. It enables calling iFlytek workflows through MCP tools.
Requires Python: >=3.11

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# iFlytek Workflow MCP Server

[The Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) 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:

```yaml
- 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](https://xinghuo.xfyun.cn/botcenter/createbot)
![](./images/create_workflow.png)

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.
![](./images/debug_workflow.png)
- **Step 4.** Select "Publish as API" and click the "Configure" button.
![](./images/publish_workflow.png)
- **Step 5.** Select the application you need to bind and bind it. Now you can retrieve the corresponding workflow ID and authentication information. Enjoy!
![](./images/bind_app.png)
> **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:

```json
{
    "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:

```json
{
    "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"
            }
        }
    }
}
```