FlowStepMCP

FlowStepMCP

Complete Model Context Protocol (MCP) server designed to facilitate seamless interaction between Large Language Models (LLMs) and end-users. It provides a robust set of tools for notifications, confirmations, selections, and text inputs, supporting multiple rendering modes including Console, GUI, and Telegram Bot.

Category
访问服务器

README

FlowStep - MCP Server for User Interactions

GitHub Version GitHub Status

🚧 Under Development

A complete Model Context Protocol (MCP) server designed to facilitate seamless interaction between Large Language Models (LLMs) and end-users. It provides a robust set of tools for notifications, confirmations, selections, and text inputs, supporting multiple rendering modes including Console, GUI, and Telegram Bot.

🎯 Native Desktop UI

▶️ Watch the demonstration video

FlowStep Demonstration

🎯 Telegram UI

▶️ Watch the demonstration video

FlowStep Demonstration

🎯 Overview

FlowStep acts as an abstraction layer for user interactions. It exposes standard MCP tools that LLMs can invoke to interact with the user based on the application's configuration (Console, GUI, or Telegram).

Key Capabilities:

  • Notifications: Display non-blocking or blocking informational messages.
  • Confirmations: Request explicit Yes/No or Cancel confirmation from the user.
  • Single & Multi-Selection: Provide dropdowns or lists for choosing one or multiple options.
  • Text Input: Collect free-form text from the user with multi-line support.
  • Custom Input: Allow selection from a predefined list or custom text entry.
  • Progress Reporting: Visual feedback for long-running operations.
  • Multiple Render Modes: Console (CLI), Desktop GUI (Avalonia), or Telegram Bot.

📦 Project Structure

The library is organized into logical layers:

FlowStep.MCP.Library/
├── Models/
│   └── InteractionModels.cs           # Data models (InteractionRequest, InteractionResponse, InteractionOption)
├── Contracts/
│   ├── IFlowStepService.cs            # Core service interface
│   └── IInteractionRenderer.cs        # Renderer interface (Contracts for UI implementation)
├── Services/
│   └── FlowStepService.cs             # Business logic and orchestration
├── McpServices/
│   └── FlowStepMcpService.cs          # Implementation of MCP Server Tools
├── Renderers/
│   ├── CliInteractionRenderer.cs      # Console-based implementation
│   ├── TelegramRenderer.cs            # Telegram Bot implementation
│   ├── GuiInteractionBridge.cs        # Bridge for custom GUI implementations
│   └── AvaloniaUI/
│       ├── AvaloniaUIRenderer.cs      # Main Avalonia GUI renderer
│       ├── Themes/
│       │   └── ThemeColors.cs         # Dark mode color definitions
│       ├── Header/
│       │   └── HeaderContentFactory.cs
│       ├── Footer/
│       │   ├── StandardFooterFactory.cs
│       │   └── NotificationFooterFactory.cs
│       ├── Inputs/
│       │   ├── SingleChoiceInputFactory.cs
│       │   ├── MultiChoiceInputFactory.cs
│       │   ├── TextInputFactory.cs
│       │   └── ChoiceWithTextInputFactory.cs
│       ├── Factories/
│       │   ├── ConfirmationButtonsFactory.cs
│       │   ├── SimpleConfirmationContentFactory.cs
│       │   └── ResponseBuilder.cs
│       └── Styles/
│           └── DarkThemeStyles.cs     # XAML-like styling logic
├── Extensions/
│   └── FlowStepServiceExtension.cs    # DI Registration helper
└── FlowStep.MCP.Library.csproj

🖥️ Rendering Modes

FlowStep supports three rendering modes, configurable at startup:

Mode Description Use Case
CLI Console/Terminal interface Headless servers, debugging, automation scripts
GUI Avalonia Desktop application Rich desktop experience with modern dark UI
Telegram Telegram Bot integration Remote interactions, mobile notifications, distributed teams

Mode Selection Priority

Configuration is resolved in the following order (highest to lowest priority):

  1. Command Line Arguments
  2. Environment Variables (prefix: FLOWSTEP_)
  3. appsettings.json
  4. Default (GUI)

⚙️ Configuration

Command Line Arguments

# GUI Mode (default)
dotnet run

# CLI Mode
dotnet run -- --mode cli

# Telegram Mode
dotnet run -- --mode telegram --telegram-token "123456:ABC-DEF" --telegram-chat-id 123456789

# Custom configuration file
dotnet run -- --config /path/to/custom-config.json

Environment Variables

# Windows
set FLOWSTEP_MODE=telegram
set FLOWSTEP_TELEGRAM__BOTTOKEN=123456:ABC-DEF
set FLOWSTEP_TELEGRAM__CHATID=123456789

# Linux/Mac
export FLOWSTEP_MODE=telegram
export FLOWSTEP_TELEGRAM__BOTTOKEN=123456:ABC-DEF
export FLOWSTEP_TELEGRAM__CHATID=123456789

appsettings.json

{
  "Logging": {
    "LogLevel": {
      "Default": "Information",
      "Microsoft.AspNetCore": "Warning"
    }
  },
  "AllowedHosts": "*",
  "Mode": "gui",
  "Telegram": {
    "BotToken": "123456:ABC-DEF",
    "ChatId": "123456789"
  }
}

Environment-Specific Configuration

Create appsettings.Development.json or appsettings.Production.json for environment-specific overrides:

{
  "Mode": "cli",
  "Logging": {
    "LogLevel": {
      "Default": "Debug"
    }
  }
}

🌐 MCP Client Configuration

To integrate FlowStep with your favorite AI editor or client (e.g., Cursor, Windsurf, Claude Desktop, or Cline), add the server configuration to your client's settings.

HTTP Transport (Recommended)

{
  "mcpServers": {
    "FlowStep.MCP": {
      "url": "http://localhost:59170"
    }
  }
}

STDIO Transport (Local Execution)

{
  "mcpServers": {
    "FlowStep.MCP": {
      "command": "dotnet",
      "args": [
        "run",
        "--project",
        "src/FlowStep.MCP/FlowStep.MCP.csproj",
        "--",
        "--mode",
        "gui"
      ]
    }
  }
}

🛠️ MCP Tools Reference

All tools are exposed via the FlowStepMcpService and automatically registered with the MCP server.

1. NotifyUserAsync

Displays a simple notification to the user with a title and message.

  • Parameters:
    • message (string): Message to be displayed to the user.
    • title (string): Notification title (optional; default: 'System').
    • waitConfirmation (bool): If true, waits for user confirmation. Default: false.
  • Returns: Status of the operation.

2. ConfirmAsync

Requests user confirmation with a message.

  • Parameters:
    • message (string): Confirmation message to the user.
    • title (string): Confirmation title (optional).
    • isCancellable (bool): Indicates whether the operation can be cancelled (optional; default: true).
  • Returns: "yes", "no", or "cancelled".

3. ChooseOptionAsync

Allows the user to choose one option among several available ones.

  • Parameters:
    • message (string): Message describing the available options.
    • options (List<InteractionOption>): List of options available for selection.
    • title (string): Title of the choice (optional).
    • allowCustomInput (bool): Whether to allow a custom input option (optional; default: false).
  • Returns: Value of the selected option or "custom:{value}" if custom input is provided.

4. ChooseMultipleOptionsAsync

Allows the user to select multiple options.

  • Parameters:
    • title (string): Title of the selection (optional).
    • message (string): Message describing the available options.
    • options (List<InteractionOption>): List of options available for selection.
    • minSelections (int): Minimum number of required selections (optional; default: 0).
    • maxSelections (int): Maximum number of allowed selections (optional; default: 1).
  • Returns: List of values of selected options.

5. AskUserForTextAsync

Requests that the user type free-form text. Supports multi-line input in GUI mode.

  • Parameters:
    • message (string): Instruction or message to the user.
    • title (string): Title of the text field (optional).
    • placeholder (string): Placeholder text shown in the input field (optional; default: 'Type here...').
  • Returns: The text entered by the user (may contain line breaks).

6. ChooseWithCustomTextAsync

Allows the user to choose one option and optionally type a custom text.

  • Parameters:
    • message (string): Instruction message for the user.
    • options (List<InteractionOption>): List of options available for selection.
    • title (string): Title of the interaction (optional).
    • placeholder (string): Placeholder text for the custom text input field (optional).
  • Returns: Selected option value or custom text prefixed with "custom:".

7. ShowProgressAsync

Displays a notification indicating the progress of an operation.

  • Parameters:
    • operationName (string): Descriptive name of the ongoing operation.
    • total (int): Total number of items to process.
    • status (string): Current status or progress message.
  • Returns: Status of the operation.

🎨 Interaction Types

The library handles six distinct interaction types defined in InteractionType:

  1. Notification: Simple display (OK).
  2. Confirmation: Yes/No decision.
  3. SingleChoice: Dropdown / Radio (Select 1).
  4. MultiChoice: Checkboxes (Select N).
  5. TextInput: Multi-line text input with word wrapping.
  6. ChoiceWithText: Predefined options + Custom text field.

🏗️ Architecture

  • Service Layer: FlowStepService handles orchestration and timeout management.
  • Renderer Layer: IInteractionRenderer defines the contract. Implementations include:
    • CliInteractionRenderer: Terminal/console interface
    • AvaloniaUIRenderer: Modern desktop GUI with dark theme
    • TelegramRenderer: Telegram Bot API integration
  • MCP Layer: FlowStepMcpService exposes tools conforming to the Model Context Protocol.

🚀 Getting Started

Prerequisites

  • .NET 10.0 SDK
  • (Optional) Telegram Bot Token for Telegram mode

Running in GUI Mode (Default)

dotnet run --project src/FlowStep.MCP/FlowStep.MCP.csproj

Running in CLI Mode

dotnet run --project src/FlowStep.MCP/FlowStep.MCP.csproj -- --mode cli

Running in Telegram Mode

# Via arguments
dotnet run --project src/FlowStep.MCP/FlowStep.MCP.csproj -- --mode telegram --telegram-token "YOUR_TOKEN" --telegram-chat-id 123456789

# Via environment
export FLOWSTEP_MODE=telegram
export FLOWSTEP_TELEGRAM__BOTTOKEN="YOUR_TOKEN"
export FLOWSTEP_TELEGRAM__CHATID=123456789
dotnet run --project src/FlowStep.MCP/FlowStep.MCP.csproj

License

This project is licensed under the MIT License - see the LICENSE file for details.

<p align="center">Made with ❤️</p>

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选