MCP提交

MCP Server Conversation Agents

一个为Google Dialogflow CX设计的MCP服务器实现，提供AI助手与Dialogflow CX之间的无缝集成。

人工智能聊天机器人客户支持 #对话集成 #意图识别 #会话管理 #语音处理 .Python

2.5分

2025-04-28 21:17:25

概述

内容详情

替代品

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 EnvironmentInstall Docker or Python 3.12+ on your system

Get Google Cloud CredentialsCreate a service account in Google Cloud Console with Dialogflow CX access

Configure the ServerSet your project details as environment variables or in a config file

Start the ServerRun 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?Basic technical knowledge is helpful for setup, but the server handles the complex parts automatically once running.

Can I use this with my existing chatbot?Yes, the MCP server is designed to work alongside your current AI assistant as an enhancement.

What audio formats are supported?Common formats like WAV with standard encoding (LINEAR16) at 16000Hz sample rate work best.

Helpful Resources

Dialogflow CX DocumentationOfficial Google documentation for Dialogflow CX

Example ImplementationSample code repository for the MCP server

Google Cloud Setup GuideInstructions for setting up Google Cloud services

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🤖 Dialogflow CX MCP 服务器 💡

一个用于管理 Dialogflow CX 会话的 MCP 服务器，支持多种交互方式和 webhook 集成。

📋 功能特性

🌟 核心功能

意图匹配：通过文本或音频输入识别用户意图。
上下文管理：维护对话状态，处理参数更新。
多轮对话：支持复杂交互流程，保持会话连贯性。
webhook 集成：与第三方服务无缝对接。

🎯 扩展功能

自定义规则：灵活配置意图路由和参数处理逻辑。
日志跟踪：记录每一步操作，便于调试和分析。
状态恢复：断线重连，确保会话不中断。

🔧 安装指南

🌐 环境要求

操作系统：Linux/MacOS/Windows（推荐使用 Linux）
Python 版本：3.8 或以上版本
依赖管理工具：pip

💽 项目安装

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

🛠️ 配置说明

将以下内容添加到 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'

🏷️ 快速上手

🚀 启动服务

python3 server.py

🔗 示例交互

文本输入

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

音频处理

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

📄 响应格式

💡 示例响应

{
  "messages": [
    {
      "type": "text",
      "content": "欢迎光临！有什么我可以帮您的吗？"
    }
  ],
  "intent": {
    "name": "greeting",
    "confidence": 0.95
  },
  "parameters": {
    "user_name": "John"
  },
  "current_page": "WelcomePage",
  "session_id": "user_123",
  "end_interaction": false
}