MCP Notify Server
📢 MCP 알림 서버
에이전트의 업무가 완료되면 사운드 효과와 함께 데스크톱 알림을 보내는 MCP 서버입니다.
🥩 특징
에이전트 작업 완료 후 시스템 데스크톱 알림 보내기
사용자의 주의를 끌기 위해 사운드 파일을 사용하여 경고음을 재생합니다.
크로스 플랫폼 지원(Windows, macOS, Linux)
표준 MCP 프로토콜을 기반으로 다양한 LLM 클라이언트와 통합됩니다.
Related MCP server: Notifications MCP Server
⏬ 설치
uv 패키지 관리자를 사용하여 설치
지엑스피1
설치 후 모듈을 직접 호출하여 설치가 성공했는지 확인하세요.
python -m mcp_server_notify이 모듈은 --debug 또는 --file 옵션을 허용하며, 다음과 같이 사용할 수 있습니다.
python -m mcp_server_notify --debug
python -m mcp_server_notify --debug --log-file=path/to/logfile.log⚠️❕ 특별 요구 사항
** 데스크톱 알림 전달을 위해 Apprise API를 사용하므로 데스크톱에 몇 가지 특별 요구 사항을 설치해야 합니다.**
윈도우
# windows:// minimum requirements
pip install pywin32맥OS
# Make sure terminal-notifier is installed into your system
brew install terminal-notifier📚 사용법
Claude Desktop과 함께 사용:
구성 파일 claude_desktop_config.json 찾으세요
{
"mcpServers": {
"NotificationServer": {
"command": "uv",
"args": [
"--directory",
"path/to/your/mcp_server_notify project",
"run",
"mcp-server-notify",
]
}
}
}글로벌하게 설치한 경우 python 명령을 사용할 수도 있습니다.
{
"mcpServers": {
"NotificationServer": {
"command": "python",
"args": [
"-m",
"mcp_server_notify",
]
}
}
}⚡️ 커서와 함께 사용:
구성 파일 ~/.cursor/mcp.json 또는 your_project/.cursor/mcp.json 찾으세요.
{
"mcpServers": {
"NotificationServer": {
"command": "uv",
"args": [
"--directory",
"path/to/your/mcp_server_notify project",
"run",
"mcp-server-notify",
]
}
}
}구성 후, finally, send me a notification when task finished. 작업 입력이 끝나면 AI에 알림을 보내줍니다.
커서에서 Cursor Settings -> Rules 에 이 프롬프트를 규칙으로 추가하면 매번 수동으로 입력할 필요가 없습니다.
⚡️ VSCode + Copilot과 함께 사용:
서비스 관리자 uv/uvx 설치:
pip install uvVSCode 설정에 서비스를 추가합니다.
윈도우
%APPDATA%\Code\User\settings.json
macOS$HOME/Library/Application\ Support/Code/User/settings.json
리눅스$HOME/.config/Code/User/settings.json"mcp": { "servers": { "notifier": { "command": "uvx", "args": [ "mcp-server-notify" ], "env": {} } } }최신 VSCode 버전을 사용하고 있는지 확인하세요. 이 버전은 MCP 서비스를 자동으로 실행합니다.
VSCode를 열고 → Copilot을 활성화하고 → 에이전트 모드로 전환합니다.
#을 입력하세요 → #send_notification 옵션이 표시됩니다.
상담원에게 문의하세요: #send_notification을 실행하세요(알림이 자동으로 처리됩니다).
이제 에이전트 모드의 Copilot이 데스크톱 알림을 보낼 수 있습니다.
🐳 Docker로 실행하기
현재 환경 호환성 문제로 인해 사용할 수 없습니다. Docker 컨테이너가 호스트 OS가 Windows, macOS, Linux인지 여부와 관계없이 호스트 알림을 트리거해야 하는 경우, 솔루션이 훨씬 더 복잡해지고 네이티브 알림을 직접 사용하는 것은 일반적으로 불가능합니다.
주요 이슈:
OS별 알림 시스템 각 운영 체제(Windows, macOS, Linux)에는 고유한 알림 메커니즘이 있습니다.
Docker 격리 Docker 컨테이너의 격리는 호스트 운영 체제 리소스에 직접 액세스하는 기능을 제한합니다.
종속성 관리 각 운영체제에 대한 다양한 알림 라이브러리와 종속성을 처리해야 합니다.
🧾 라이센스
MIT
💻 기여
이슈와 풀 리퀘스트를 환영합니다!
Available Tools
1 toolsend_notificationC
Send system notification with optional sound
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | ||
| message | Yes | ||
| play_sound | No | ||
| timeout | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool sends a notification but doesn't disclose behavioral traits like whether it's synchronous/asynchronous, what happens on failure, if it requires specific permissions, or how notifications are delivered. 'Optional sound' hints at a feature but lacks details on default behavior or sound types.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that directly states the tool's function. It's front-loaded and wastes no words, making it easy to parse quickly. Every part of the sentence contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0% schema description coverage for 4 parameters, the description is incomplete. It covers the basic action but lacks details on behavior, parameters, return values, or error handling. For a notification-sending tool with multiple parameters, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description doesn't add meaning beyond what the schema provides. It mentions 'optional sound' which corresponds to the 'play_sound' parameter, but doesn't explain other parameters like 'title', 'message', or 'timeout'. With 4 parameters and no schema descriptions, the description fails to compensate adequately, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('send') and resource ('system notification') with an additional feature ('optional sound'). It's specific about what the tool does, though without sibling tools, differentiation isn't applicable. The purpose is unambiguous but could be more detailed about the notification type or system context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool, such as appropriate contexts, prerequisites, or alternatives. It mentions 'optional sound' but doesn't explain when sound should be enabled or disabled. With no sibling tools, this is less critical, but still lacks usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
send_notification
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'send_notification' has a clear, distinct purpose that cannot be confused with any other tool in the set.
The tool name 'send_notification' follows a clear verb_noun pattern (send + notification). Since there is only one tool, consistency is inherently perfect with no deviations or mixed conventions to evaluate.
A single tool is too few for a server named 'MCP Notify Server', which suggests a broader notification domain. This minimal set feels thin and likely incomplete for typical notification workflows, such as managing notifications or checking statuses.
The tool surface is severely incomplete for a notification server. While 'send_notification' covers sending, there are obvious gaps like listing notifications, updating them, deleting them, or configuring notification settings, which agents would need for full functionality.
Maintenance
Related MCP Connectors
Push notifications for AI agents - send instant iPhone notifications from any MCP client.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
Let your AI agent notify you by email, Slack, Discord, or webhook. One tool: send_notification.
Build agents to automate any background task. Works with your ChatGPT/Claude subscription.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenancemacOS Notification MCP enables AI assistants to trigger native macOS sounds, visual notifications, and text-to-speech. Built for Claude and other AI models using the Model Context Protocol.37MIT
- AlicenseBqualityCmaintenanceA Model Context Protocol server that allows AI agents to play notification sounds when tasks are completed.132 npm14Apache 2.0
- AlicenseCqualityFmaintenanceA Model Context Protocol server for macOS that enables AI assistants to play system sounds for audio feedback, offering informational, warning, and error sound options.41MIT
- AlicenseAqualityCmaintenanceA persistent state machine and notification system for AI agents to manage complex, multi-step workflows via the Model Context Protocol, preventing context drift by maintaining structured checklists and sending desktop alerts.1410 npm2Apache 2.0