Sponsored by Deepsite.site

🎵 Notification MCP: Sounding Success in AI Tasks 🎉

Created By
harunnn77746 months ago
<div align="center"> <img src="
Content

🎵 Notification MCP: Sounding Success in AI Tasks 🎉

Notification MCP

Welcome to the Notification MCP repository! This project provides a Model Context Protocol (MCP) server designed to enable AI agents to play notification sounds upon task completion. With this server, you can enhance your AI workflows by adding auditory feedback, making it easier to track task statuses.

Table of Contents

Features

  • AI Integration: Seamlessly integrate with AI agents to enhance task management.
  • Sound Notifications: Play custom sounds when tasks are completed.
  • TypeScript Support: Built using TypeScript for type safety and better development experience.
  • Node.js Compatibility: Runs on Node.js, ensuring a robust and scalable server.
  • MCP Compliance: Follows the Model Context Protocol standards for consistency and reliability.

Getting Started

To get started with the Notification MCP server, follow the steps below. Make sure you have Node.js installed on your machine.

Prerequisites

  • Node.js (version 14 or higher)
  • TypeScript (installed globally)

You can download Node.js from nodejs.org.

Installation

  1. Clone the repository:

    git clone https://github.com/harunnn7774/notification-mcp.git
    
  2. Navigate to the project directory:

    cd notification-mcp
    
  3. Install the dependencies:

    npm install
    

Usage

  1. Start the Server:

    Run the following command to start the MCP server:

    npm start
    
  2. Configure Your AI Agent:

    Your AI agent should connect to the MCP server and listen for task completion events. When an event occurs, the server will trigger the corresponding notification sound.

  3. Playing Sounds:

    You can customize the sounds that play by modifying the configuration files in the config directory. Ensure that the sound files are accessible to the server.

Example Configuration

Here’s an example configuration file for your AI agent:

{
  "agentName": "TaskNotifier",
  "serverUrl": "http://localhost:3000",
  "notificationSound": "path/to/sound/file.mp3"
}

Sample Agent Code

Below is a simple example of how your AI agent might look:

import { MCPClient } from 'mcp-client';

const client = new MCPClient('http://localhost:3000');

client.on('taskCompleted', (task) => {
  console.log(`Task ${task.id} completed!`);
  client.playSound(task.notificationSound);
});

Contributing

We welcome contributions! If you would like to contribute to the Notification MCP project, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature or bug fix.
  3. Make your changes and commit them.
  4. Push your changes to your fork.
  5. Create a pull request.

License

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

Contact

For any inquiries or support, feel free to reach out:

Releases

You can find the latest releases of the Notification MCP server here. Make sure to download the appropriate version for your needs and follow the installation instructions.

If you need further assistance, check the "Releases" section for updates and additional resources.

Conclusion

The Notification MCP server is a powerful tool for integrating sound notifications into your AI workflows. With its simple setup and clear configuration, you can enhance your applications with auditory feedback that keeps you informed about task completions.

Thank you for visiting the Notification MCP repository. We hope you find this project useful and look forward to your contributions!

Recommend Servers
TraeBuild with Free GPT-4.1 & Claude 3.7. Fully MCP-Ready.
ChatWiseThe second fastest AI chatbot™
EdgeOne Pages MCPAn MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.
AiimagemultistyleA Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.
CursorThe AI Code Editor
Howtocook Mcp基于Anduin2017 / HowToCook (程序员在家做饭指南)的mcp server,帮你推荐菜谱、规划膳食,解决“今天吃什么“的世纪难题; Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"
BlenderBlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.
TimeA Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.
MiniMax MCPOfficial MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
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。
WindsurfThe new purpose-built IDE to harness magic
Zhipu Web SearchZhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.
DeepChatYour AI Partner on Desktop
Playwright McpPlaywright MCP server
Amap Maps高德地图官方 MCP Server
MCP AdvisorMCP Advisor & Installation - Use the right MCP server for your needs
Context7Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors
Serper MCP ServerA Serper MCP Server
Visual Studio Code - Open Source ("Code - OSS")Visual Studio Code
Jina AI MCP ToolsA Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.
Tavily Mcp