iFlytek Workflow MCP Server
A server implementation of the Model Context Protocol that enables calling iFlytek workflows, supporting complex orchestration modes like sequential, parallel, and looped execution across 14 node types for diverse business scenarios.
iflytek
README
<p align="center"> <a href="https://xinghuo.xfyun.cn/botcenter/createbot"><img src="https://openres.xfyun.cn/xfyundoc/2024-04-26/1396db8a-313b-40f5-be2a-5babcad9cd64/1714102184743/sparklogo.svg"></a> </p> <p align="center"> The fastest way to build workflows with an AI agent platform! </p> <p align="center"> <a href="https://github.com/iflytek/ifly-workflow-mcp-server/blob/main/LICENSE" target="_blank"> <img src="https://img.shields.io/static/v1?label=license&message=MIT licensed&color=white" alt="License"> </a> | <a href="https://xinghuo.xfyun.cn/botcenter/createbot" target="_blank"> Docs </a> | <a href="https://xinghuo.xfyun.cn/botcenter/createbot" target="_blank"> Homepage </a> </p>
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
-
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"
}
}
}
}
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
MCP Package Docs Server
Facilitates LLMs to efficiently access and fetch structured documentation for packages in Go, Python, and NPM, enhancing software development with multi-language support and performance optimization.
Claude Code MCP
An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.
@kazuph/mcp-taskmanager
Model Context Protocol server for Task Management. This allows Claude Desktop (or any MCP client) to manage and execute tasks in a queue-based system.
Linear MCP Server
Enables interaction with Linear's API for managing issues, teams, and projects programmatically through the Model Context Protocol.
mermaid-mcp-server
A Model Context Protocol (MCP) server that converts Mermaid diagrams to PNG images.
Jira-Context-MCP
MCP server to provide Jira Tickets information to AI coding agents like Cursor

Linear MCP Server
A Model Context Protocol server that integrates with Linear's issue tracking system, allowing LLMs to create, update, search, and comment on Linear issues through natural language interactions.

Sequential Thinking MCP Server
This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.