What's the difference between scheduled and on-demand tasks?
Scheduled tasks include a cron expression and run automatically on that schedule. On-demand tasks omit the schedule and sit idle until triggered via the `run_task` tool.
@jolks
基本情報
MCP server for scheduling and running AI prompts, HTTP/webhook requests, and shell commands
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"mcp-cron": {
"command": "npx",
"args": [
"-y",
"mcp-cron"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。
MCP Cron is a Model Context Protocol server for scheduling and managing tasks through a standardized API. It supports shell commands, AI-powered tasks, and HTTP webhook tasks, with task persistence across restarts via SQLite. It's intended for developers and AI agents that need to schedule recurring or on-demand work.
Install via npx -y mcp-cron and configure it in your MCP client's config file (e.g., ~/.cursor/mcp.json or Claude Desktop's config). The server supports two transport modes: HTTP (Streamable HTTP, default) and stdio. Key command-line arguments include --transport, --ai-provider, --ai-model, --db-path, and --prevent-sleep.
run_taskScheduled tasks include a cron expression and run automatically on that schedule. On-demand tasks omit the schedule and sit idle until triggered via the `run_task` tool.
It supports HTTP (Streamable HTTP, the default) and stdio. HTTP is for browser/network clients; stdio is for direct piping and inter-process communication.
On macOS and Windows, the `--prevent-sleep` flag prevents the system from going idle while MCP Cron is running. It uses `caffeinate` on macOS and `SetThreadExecutionState` on Windows. Linux is not supported for sleep prevention.
It uses a local SQLite database. The default path is `~/.mcp-cron/results.db`, configurable with the `--db-path` flag or `MCP_CRON_STORE_DB_PATH` environment variable.
Use `--ai-provider` (openai or anthropic) and `--ai-model` flags, or their corresponding environment variables. API keys are set via `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, or the generic `MCP_CRON_AI_API_KEY`. A custom base URL (`--ai-base-url`) supports OpenAI-compatible endpoints like LiteLLM.

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