MCP Server Conversation Agents

一個為Google Dialogflow CX設計的MCP服務器實現，提供AI助手與Dialogflow CX之間的無縫集成。

人工智能聊天機器人客戶支持 #對話集成 #意圖識別 #會話管理 #語音處理 .Python

評分 : 2.5分

下載量 : 17

更新時間 : 2025-04-28

What is Dialogflow CX MCP Server?

This server acts as a communication bridge that allows AI assistants to connect with Google's Dialogflow CX platform. It handles all the complex interactions like understanding user requests, managing conversations, and processing responses from Dialogflow's powerful language understanding system.

How to use Dialogflow CX MCP Server?

You can set up the server either through Docker for quick deployment or install it manually. After configuration with your Google Cloud credentials, your AI assistant can start sending requests to Dialogflow CX through the server's API endpoints.

Use Cases

Ideal for businesses that want to enhance their AI assistants with Google's advanced conversation capabilities. Common scenarios include customer support chatbots, voice assistants, and automated appointment scheduling systems.

Key Features

Two-Way CommunicationEnables seamless back-and-forth conversations between your AI assistant and Dialogflow CX

Smart Intent RecognitionAccurately identifies what users want from their messages or voice inputs

Voice Command SupportProcesses audio inputs and converts them to understandable requests

Conversation MemoryRemembers context across multiple interactions for natural conversations

Pros and Cons

Advantages

Leverages Google's powerful natural language understanding

Handles complex conversation flows automatically

Supports both text and voice interactions

Easy integration with existing AI assistants

Limitations

Requires Google Cloud project setup

Needs configuration for optimal performance

Audio processing requires specific formats

Getting Started

Set Up Your Environment

Install Docker or Python 3.12+ on your system

Get Google Cloud Credentials

Create a service account in Google Cloud Console with Dialogflow CX access

Configure the Server

Set your project details as environment variables or in a config file

Start the Server

Run the server using Docker or directly through Python

Example Scenarios

Customer Support ChatbotHandle common customer questions about products and services

Appointment SchedulingLet users book appointments through natural conversation

Frequently Asked Questions

Do I need programming skills to use this?

Can I use this with my existing chatbot?

What audio formats are supported?

Helpful Resources

Dialogflow CX Documentation

Official Google documentation for Dialogflow CX

Example Implementation

Sample code repository for the MCP server

Google Cloud Setup Guide

Instructions for setting up Google Cloud services

🚀 🤖 Dialogflow CX MCP 服務器 💡

這是一個用於管理 Dialogflow CX 會話的 MCP 服務器，支持多種交互方式和 webhook 集成，能有效識別用戶意圖、管理對話上下文，讓對話交互更加流暢。

🚀 快速開始

啟動服務，你可以通過以下命令開啟這個強大的 MCP 服務器：

python3 server.py

示例交互：

文本輸入

curl -X POST http://localhost:5005/api/conversations \
 -H "Content-Type: application/json" \
 -d '{"text": "你好", "session_id": "user_123"}'

音頻處理

curl -X POST http://localhost:5005/api/audio \
 -H "Content-Type: audio/wav" \
 -d '@/path/to/audio.wav'

✨ 主要特性

🌟 核心功能

意圖匹配：通過文本或音頻輸入識別用戶意圖。
上下文管理：維護對話狀態，處理參數更新。
多輪對話：支持複雜交互流程，保持會話連貫性。
webhook 集成：與第三方服務無縫對接。

🎯 擴展功能

自定義規則：靈活配置意圖路由和參數處理邏輯。
日誌跟蹤：記錄每一步操作，便於調試和分析。
狀態恢復：斷線重連，確保會話不中斷。

📦 安裝指南

🌐 環境要求

操作系統：Linux/MacOS/Windows（推薦使用 Linux）
Python 版本：3.8 或以上版本
依賴管理工具：pip

💽 項目安裝

git clone https://github.com/your-repository.git
cd mcp-server
pip install -r requirements.txt

📚 詳細文檔

🛠️ 配置說明

將以下內容添加到 config.yaml 文件中：

server:
  host: '0.0.0.0'
  port: 5005
  
dialogflow:
  project_id: 'your-project-id'
  private_key_path: './path/to/service-account.json'
  
webhook:
  enable: true
  url: 'https://api.your-domain.com/webhook'

📄 響應格式

💡 示例響應

{
  "messages": [
    {
      "type": "text",
      "content": "歡迎光臨！有什麼我可以幫您的嗎？"
    }
  ],
  "intent": {
    "name": "greeting",
    "confidence": 0.95
  },
  "parameters": {
    "user_name": "John"
  },
  "current_page": "WelcomePage",
  "session_id": "user_123",
  "end_interaction": false
}