ntfy-me-mcp MCP Server

What does “ntfy-me-mcp” MCP Server do?

The ntfy-me-mcp MCP Server acts as a bridge between AI assistants and ntfy notification servers (including self-hosted or ntfy.sh instances). It enables AI agents to programmatically send and fetch notifications using the Model Context Protocol (MCP), enhancing productivity and automation in development workflows. By exposing notification operations via MCP, ntfy-me-mcp allows language models and tools to interact with notification services securely—supporting features like secure token authentication. This makes it suitable for scenarios where automated alerts, reminders, or notification-driven workflows are required, streamlining communication between external services, APIs, and AI-driven agents in a standardized way.

List of Prompts

No explicit prompt templates were listed in the repository or documentation.

List of Resources

No explicit MCP resources were documented in the repository or documentation.

List of Tools

No explicit tools were listed in server.py or the repository contents.

Use Cases of this MCP Server

• Automated Alerting
  Developers can use ntfy-me-mcp to send real-time notifications to themselves or teams when certain events occur (e.g., CI/CD builds fail, server errors, or important log entries are detected).

• AI-driven Reminders
  Integrate with AI assistants to schedule and deliver reminders or actionable alerts via ntfy, automating personal or team productivity workflows.

• Notification-based Triggers
  Use AI agents to trigger actions when specific notifications are received, such as escalating incidents, initiating follow-up workflows, or updating dashboards.

• Cross-platform Notifications
  Send notifications from various AI-driven tools or bots to any ntfy-compatible client (mobile, desktop, browser), ensuring messages reach users wherever they are.

How to set it up

Windsurf

1. Prerequisites: Ensure Node.js is installed.
2. Edit Configuration: Locate your .windsurf/settings.json or platform-specific config file.
3. Add ntfy-me-mcp Server: Insert into mcpServers:

   {
     "ntfy-me-mcp": {
       "command": "npx",
       "args": ["@gitmotion/ntfy-me-mcp@latest"]
     }
   }
   

4. Save and Restart: Save config and restart Windsurf.
5. Verify: Check that ntfy-me-mcp is running and available as an MCP server.

Securing API Keys Example (env section):

{
  "ntfy-me-mcp": {
    "command": "npx",
    "args": ["@gitmotion/ntfy-me-mcp@latest"],
    "env": {
      "NTFY_AUTH_TOKEN": "${env.NTFY_AUTH_TOKEN}"
    },
    "inputs": {
      "NTFY_SERVER": "https://ntfy.sh"
    }
  }
}

Claude

1. Prerequisites: Ensure Node.js is installed.
2. Configuration File: Open the MCP config (e.g., .claude/mcp.json).
3. Add MCP Server:

   {
     "ntfy-me-mcp": {
       "command": "npx",
       "args": ["@gitmotion/ntfy-me-mcp@latest"]
     }
   }
   

4. Restart Claude.
5. Check Integration.

Cursor

1. Prerequisites: Node.js installed.
2. Open Cursor Config: (.cursor/settings.json)
3. Add MCP Server:

   {
     "ntfy-me-mcp": {
       "command": "npx",
       "args": ["@gitmotion/ntfy-me-mcp@latest"]
     }
   }
   

4. Save and Restart Cursor.
5. Validate Setup.

Cline

1. Prerequisites: Node.js installed.
2. Edit cline.config.json.
3. Insert MCP Server:

   {
     "ntfy-me-mcp": {
       "command": "npx",
       "args": ["@gitmotion/ntfy-me-mcp@latest"]
     }
   }
   

4. Restart Cline.
5. Confirm MCP is available.

Note:
To secure API keys, always use the env section in your configuration. Example:

{
  "ntfy-me-mcp": {
    "command": "npx",
    "args": ["@gitmotion/ntfy-me-mcp@latest"],
    "env": {
      "NTFY_AUTH_TOKEN": "${env.NTFY_AUTH_TOKEN}"
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "ntfy-me-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “ntfy-me-mcp” to the actual name of your MCP server and replace the URL with your own MCP server URL.

Overview

Based on the above tables, ntfy-me-mcp gets a modest score. It delivers clear value for notification workflows, but lacks documentation or code for MCP prompt templates, resources, or tools, and does not mention advanced MCP features like roots or sampling.

MCP Score