Toast MCP Server – Desktop Notification Service for AI Workflows

The Toast MCP Server fills a niche that many developers and data‑science teams encounter when integrating AI assistants into their local development environments: how can an assistant reliably surface information on the user’s desktop without requiring a full‑blown UI framework? This server answers that question by exposing a lightweight Model Context Protocol (MCP) endpoint that turns any MCP‑compatible client—such as VS Code’s Cline extension—into a trigger for system notifications on Windows 10 and macOS.

At its core, the server implements the MCP specification so that clients can send simple “notify” commands. Upon receipt, the server translates those commands into native desktop notifications using on Windows and AppleScript () on macOS. The notification payload is fully configurable: title, message body, duration, icon (Windows only), subtitle and sound (macOS only), and a type flag that lets the client choose between informational, warning, error, or success styles. This flexibility means developers can surface build status updates, model inference results, or even error alerts directly on the desktop while they continue coding.

For developers, this translates into several practical advantages:

• Zero‑friction integration – Because the server speaks MCP, any existing client that already supports the protocol can immediately leverage notifications without additional SDKs or APIs.
• Cross‑platform consistency – The same MCP command works on both Windows 10 and macOS, allowing teams with mixed operating systems to share notification logic.
• Asynchronous workflow support – The server handles both synchronous and asynchronous requests, enabling long‑running AI tasks to push alerts back to the user as soon as they finish.
• Security and reliability – Configurable host/port settings (default 127.0.0.1:8000, with support for 0.0.0.0) and robust error handling keep the service safe from malformed requests while providing detailed logs for debugging.

Typical use cases include:

• Continuous integration pipelines – A CI job can send a success or failure notification to the developer’s desktop once a build completes.
• Model training monitoring – Long‑running machine‑learning experiments can push progress updates or final metrics without requiring the user to open a browser window.
• Chatbot interactions – An AI assistant can deliver reminders or important messages directly to the user’s notification center, keeping context close at hand.
• IDE extensions – Plugins that rely on MCP can now use the server to surface linting errors, test results, or code review comments instantly.

Integration is straightforward: run the Python 3.8+ server, point your MCP client to its address, and issue a command with the desired parameters. The server’s async architecture ensures that multiple clients can connect simultaneously, and its comprehensive logging makes troubleshooting trivial. By turning an MCP client into a desktop notifier, the Toast MCP Server removes one of the last barriers to fully immersive AI‑augmented development workflows.