mcp_server_alert_hub
Facilitates the dispatch of auditory alerts and visual desktop pop-ups immediately following the finalization of autonomous agent operations, thus improving operator engagement through prompt feedback mechanisms. Compatible with diverse Large Language Model clients operating across Windows, MacOS, and Linux environments.
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Cactusinhand
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📢 MCP Notify Server
English | 中文
A MCP backend component designed to issue system desktop alerts alongside audible signals upon the successful termination of assigned agent workflows.
🥩 Core Capabilities
- Broadcast system-level graphical alerts subsequent to agent task conclusion.
- Emit attention-grabbing audio cues, bundled with the necessary sound asset files.
- Operational parity across major operating systems (Windows, macOS, Linux).
- Adheres to the standard Message Communication Protocol (MCP), enabling seamless integration with various AI computation interfaces.
⏬ Acquisition and Setup
Installation via the [uv] package manager
bash git clone https://github.com/Cactusinhand/mcp_server_notify.git cd mcp_server_notify
uv venv source .venv/Scripts/activate
uv pip install mcp-server-notify
Alternatively:
pip install mcp-server-notify
Verify the setup success by executing the installed module directly: bash python -m mcp_server_notify
This utility accepts optional flags such as --debug or --file for enhanced operational visibility:
shell
python -m mcp_server_notify --debug
python -m mcp_server_notify --debug --log-file=path/to/logfile.log
⚠️❕ Prerequisite Dependencies
** Notification delivery relies upon the [Apprise] API framework; consequently, specific platform requirements must be satisfied on the host Desktop environment **
Windows Users shell
Required for windows:// protocol handling
pip install pywin32
macOS Users shell
Ensure the terminal-notifier utility is present on the system
brew install terminal-notifier
📚 Operational Integration Guide
Configuration for Claude Desktop Clients:
Modify the configuration file named claude_desktop_config.json:
{ "mcpServers": { "NotificationServer": { "command": "uv", "args": [ "--directory", "path/to/your/mcp_server_notify project", "run", "mcp-server-notify", ] } } }
If the package is installed system-wide, the standard Python execution path can be utilized instead:
{ "mcpServers": { "NotificationServer": { "command": "python", "args": [ "-m", "mcp_server_notify", ] } } }
Once configured, instruct the AI agent via a directive such as finally, send me a notification when task finished. appended to your instruction set to activate the alert functionality.
In the Cursor editor, this instruction can be permanently stored as a defined rule within Cursor Settings -> Rules to eliminate manual repetition.
⚡️ Integration with Cursor Editor:
Refer to configuration file locations: ~/.cursor/mcp.json or your_project/.cursor/mcp.json
{ "mcpServers": { "NotificationServer": { "command": "uv", "args": [ "--directory", "path/to/your/mcp_server_notify project", "run", "mcp-server-notify", ] } } }
⚡️ Interfacing with VSCode + Copilot:
- Install the orchestration utility manager [uv/uvx]:
pip install uv -
Embed the service definition within VSCode user settings:
Windows:
%APPDATA%\Code\User\settings.json
macOS:$HOME/Library/Application\ Support/Code/User/settings.json
Linux:$HOME/.config/Code/User/settings.json"mcp": { "servers": { "notifier": { "command": "uvx", "args": [ "mcp-server-notify" ], "env": {} } } }
-
Ensure VSCode is running its latest stable release; service execution is automatic.
- Launch VSCode → activate Copilot → switch to agent operational mode.
- Invoke command input with
#→ the#send_notificationoption will become visible. - Request the agent: execute
#send_notification(this triggers the notification workflow). - Desktop alerts are now actionable via Copilot's agent interface.
🐳 Docker Deployment Status
Currently unavailable due to complexities associated with achieving host notification access from within isolated container environments. Achieving reliable host-level alerts (across Windows, macOS, and Linux) from a standard Docker setup presents significant hurdles, primarily due to:
- Dependence on OS-specific notification APIs.
- Inherent isolation of containerized processes from the host OS surface.
- Complicated dependency resolution for platform-specific notification libraries.
🧾 Licensing
MIT
💻 Community Engagement
Feedback, issues, and contributions are enthusiastically welcomed!
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