MCP Scheduler

A robust task scheduler server built with Model Context Protocol (MCP) for scheduling and managing various types of automated tasks.

Overview

MCP Scheduler is a versatile task automation system that allows you to schedule and run different types of tasks:

• Shell Commands: Execute system commands on a schedule
• API Calls: Make HTTP requests to external services
• AI Tasks: Generate content through OpenAI models
• Reminders: Display desktop notifications with sound

The scheduler uses cron expressions for flexible timing and provides a complete history of task executions. It's built on the Model Context Protocol (MCP), making it easy to integrate with AI assistants and other MCP-compatible clients.

Features

• Multiple Task Types: Support for shell commands, API calls, AI content generation, and desktop notifications
• Cron Scheduling: Familiar cron syntax for precise scheduling control
• Run Once or Recurring: Option to run tasks just once or repeatedly on schedule
• Execution History: Track successful and failed task executions
• Cross-Platform: Works on Windows, macOS, and Linux
• Interactive Notifications: Desktop alerts with sound for reminder tasks
• MCP Integration: Seamless connection with AI assistants and tools
• Robust Error Handling: Comprehensive logging and error recovery

Installation

Prerequisites

• Python 3.10 or higher
• uv (recommended package manager)

Installing uv (recommended)

# For Mac/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# For Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

After installing uv, restart your terminal to ensure the command is available.

Project Setup

# Clone the repository
git clone https://github.com/phialsbasement/mcp-scheduler.git
cd mcp-scheduler

# Create and activate a virtual environment with uv
uv venv
source .venv/bin/activate  # On Unix/MacOS
# or
.venv\Scripts\activate     # On Windows

# Install dependencies with uv
uv pip install -r requirements.txt

Standard pip installation (alternative)

If you prefer using standard pip:

# Clone the repository
git clone https://github.com/phialsbasement/mcp-scheduler.git
cd mcp-scheduler

# Create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate  # On Unix/MacOS
# or
.venv\Scripts\activate     # On Windows

# Install dependencies
pip install -r requirements.txt

Usage

Running the Server

# Run with default settings (stdio transport)
python main.py

# Run with server transport on specific port
python main.py --transport sse --port 8080

# Run with debug mode for detailed logging
python main.py --debug

Integrating with Claude Desktop or other MCP Clients

To use your MCP Scheduler with Claude Desktop:

1. Make sure you have Claude Desktop installed
2. Open your Claude Desktop App configuration at:
   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json
3. Create the file if it doesn't exist, and add your server:

{
  "mcpServers": [
    {
      "type": "stdio",
      "name": "MCP Scheduler",
      "command": "python",
      "args": ["/path/to/your/mcp-scheduler/main.py"]
    }
  ]
}

Alternatively, use the fastmcp utility if you're using the FastMCP library:

# Install your server in Claude Desktop
fastmcp install main.py --name "Task Scheduler"

Command Line Options

--address        Server address (default: localhost)
--port           Server port (default: 8080)
--transport      Transport mode (sse or stdio) (default: stdio)
--log-level      Logging level (default: INFO)
--log-file       Log file path (default: mcp_scheduler.log)
--db-path        SQLite database path (default: scheduler.db)
--config

... [View full README on GitHub](https://github.com/PhialsBasement/scheduler-mcp#readme)