MCP server for desktop notifications over stdio
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Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-topvisor-mcp-notifications": {
"args": [
"-y",
"@topvisor/mcp-notifications"
],
"command": "npx"
}
}
}From the project's GitHub README.
๐ Ship faster. Miss nothing.
mcp-notifications lets your MCP agent send desktop notifications for completed tasks, failures, and important updates.
This is especially useful for console AI agents, because they usually have no built-in notifications by default.
No more checking chats every minute.
No more silent agent responses.
Just visible, reliable feedback on your desktop. ๐
You give tasks to several AI agents, then wait and keep checking who already replied.
With mcp-notifications, this gets simpler: the agent can notify you on desktop when it needs your input or when work
is done.
node-notifier.Requirements:
>=20>=10npm i -g @topvisor/mcp-notifications
Executable name (use this in MCP config):
mcp-notifications
mcp-notifications is an MCP server entrypoint (stdio), not a one-shot notification command.
Add this to ~/.codex/config.toml:
[mcp_servers.notifications]
enabled = true
command = "mcp-notifications"
args = []
Restart Codex after config update.
Add MCP server config to your Claude client config file:
{
"mcpServers": {
"notifications": {
"command": "mcp-notifications",
"args": []
}
}
}
Then restart Claude client.
There are two approaches to notifications: manual and automatic.
Choose the one that works better for your workflow.
In a task where you want to be notified, explicitly ask the agent. Example:
Count files in the project; after the task is fully complete, notify me with sound.
You can also define sound, topic, and frequency rules inside a specific chat. Example:
Notify me about your replies without sound, include the reply text, and use title: "Large Refactoring"
Automatic notifications can be configured globally or per project.
Example instruction to enable automatic notifications for agent replies:
Send `send_notification` after your replies (actual task time >5 seconds or many steps); `play_sound: false`; `app_id: '{put your chat name here}'`
Time is a rough threshold and depends on model behavior, so adjust this instruction to your own preferences.
You can also enable notifications in specific skills. Example for a Review skill:
After the review, run `send_notification` with a short summary; `play_sound: true`; `app_id: 'Reviewer {put task id here}'`
send_notificationInput:
title string (required)message string (required)play_sound boolean (optional, default: false)icon string (optional, absolute or relative path to image file)app_id string (optional, Windows App User Model ID for toast source)Example:
{
"title": "Codex",
"message": "Deployment completed successfully",
"play_sound": true,
"icon": "/opt/mcp-notifications/icons/custom.png",
"app_id": "Topvisor.Codex"
}
app_id controls the source shown in Windows toast notifications.app_id is not set, Windows may show SnoreToast as the source.app_id in each tool call, or set MCP_NOTIFICATIONS_APP_ID as an environment variable for the server.Use these messages directly in chat:
Check send_notification
Send a notification without sound: title "Test", message "Check"
Send a notification with sound: title "Test", message "Check"
Send a notification with app_id "Topvisor.Codex": title "Test", message "Check"
Send 3 test notifications in a row without sound
Expected tool result in logs/response:
Notification queued
play_sound: true.The AI agent is waiting for you:

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