ntfy-me-mcp

ntfy‑me‑mcp is an MCP server that bridges AI assistants with a self‑hosted ntfy notification service. It solves the common problem of reliably pushing alerts, logs, or status updates from AI workflows to a dedicated notification endpoint without exposing sensitive credentials. By encapsulating the ntfy API behind MCP, developers can invoke notifications as a first‑class tool in their AI pipelines, ensuring consistent authentication and lightweight communication.

The server exposes a single, straightforward capability: send notification. When an AI assistant calls this endpoint with a message payload, the server authenticates using a bearer token and forwards the text to the configured ntfy instance. This design keeps the notification logic isolated from client code, allowing teams to manage tokens centrally and audit traffic through a single entry point. The lightweight architecture consumes minimal resources, making it ideal for containerized deployments on edge devices or cloud functions.

Key features include:

• Secure token authentication that prevents unauthorized messages and protects user data.
• Docker support, enabling rapid deployment in CI/CD pipelines or Kubernetes clusters.
• Cross‑platform compatibility (Linux, Windows) so that any development environment can host the server.
• Minimal configuration, requiring only a token and ntfy URL, which keeps setup fast for developers.

Typical use cases involve:

• Real‑time monitoring of AI model training jobs, where progress or error alerts are sent to a team channel.
• Workflow orchestration in automated data pipelines, triggering notifications when stages complete or fail.
• Developer feedback loops, where an assistant can ping a developer’s phone with code review reminders or build statuses.

Integration into AI workflows is seamless: an MCP‑enabled assistant simply invokes the send tool with a message string, and the server handles the HTTP request to ntfy. Because MCP abstracts the underlying protocol, developers can swap notification backends or add additional security layers without changing assistant code. This plug‑and‑play nature gives teams flexibility to evolve their notification infrastructure while keeping AI interactions consistent.