ntfy-mcp is an MCP server designed to provide real-time notifications upon AI task completion, leveraging the ntfy platform. By integrating seamlessly with the Model Context Protocol, ntfy-mcp acts as a notification relay, informing users when their AI assistant finishes a task. This eliminates the need for constant monitoring, allowing developers to focus on other critical activities.

The server utilizes the @modelcontextprotocol/sdk, node-fetch, dotenv, and zod libraries to manage MCP interactions and notification delivery. To use it, developers configure ntfy-mcp with their desired ntfy topic and integrate it into their MCP client setup. Once configured, the AI model can trigger notifications through the MCP, which are then relayed to the user's ntfy app. The core value lies in its ability to keep users informed without disrupting their workflow, enhancing productivity and responsiveness.

Real-time Task Completion Alerts

ntfy-mcp's core function is to provide real-time notifications upon the completion of tasks executed by an AI model. This is achieved by monitoring the AI model's processes through the Model Context Protocol (MCP). Once the AI model signals task completion, ntfy-mcp triggers a notification via the ntfy service, which is then relayed to the user's subscribed device (e.g., smartphone, desktop). This ensures users are promptly informed without needing to actively monitor the AI's progress. For example, a developer waiting for an AI to finish generating code can receive an instant notification on their phone, allowing them to switch to other tasks without constantly checking the AI's output. This feature enhances productivity and reduces unnecessary waiting time. The server utilizes @modelcontextprotocol/sdk to interact with the AI model and node-fetch to send the notification to ntfy.

Seamless ntfy Integration

ntfy-mcp leverages the ntfy service to deliver notifications, offering a straightforward and efficient way to keep users informed. The integration is designed to be seamless, requiring minimal configuration. Users simply subscribe to a specific topic on the ntfy app, and ntfy-mcp publishes notifications to that topic upon task completion. This eliminates the need for complex notification setups or custom integrations with other messaging services. For instance, a data scientist running a long-running AI model training job can receive a notification via ntfy when the training is complete, even if they are away from their computer. The simplicity of the ntfy integration makes ntfy-mcp easy to deploy and use, even for users with limited technical expertise. The server uses environment variables, specifically NTFY_TOPIC, to configure the ntfy topic.

Simplified Workflow with Cline

ntfy-mcp can be easily integrated with Cline, streamlining the workflow for developers and users. By configuring Cline to use ntfy-mcp as an MCP server, AI models can automatically trigger notifications upon task completion without requiring manual intervention. This integration simplifies the process of receiving updates on AI model activities, making it easier to manage and monitor AI-driven tasks. For example, in a CI/CD pipeline, an AI model could be used to automatically analyze code quality. With ntfy-mcp and Cline, developers can receive instant notifications when the analysis is complete, allowing them to quickly address any issues. The autoApprove feature in Cline configuration ensures that the notify_user action is automatically approved, further simplifying the user experience.