A robust task scheduler server built with Model Context Protocol for scheduling and managing various types of automated tasks including shell commands, API calls, AI tasks, and reminders.
Enables AI tools to manage and operate the sched cron scheduler via the Model Context Protocol, including task scheduling, monitoring, and configuration.
An MCP server that lets AI agents manage cron jobs through natural language — adding, listing, pausing, removing, running, and viewing logs of scheduled jobs with plain-English schedule parsing, automatic log capture, missed-run detection, and failure alerts.
An MCP server that surfaces scheduled-job state and detects silent failures (exit 0 but no useful output) for cron, systemd timers, and OpenClaw schedulers, enabling AI agents to query job health and overdue status directly.
Enables creation and management of scheduled tasks with interval, cron, or one-time triggers. Persists tasks in SQLite and supports MCP sampling to automatically invoke AI agents when schedules trigger.
An MCP server for scheduling and executing Claude Code CLI tasks via cron expressions, featuring a web dashboard and webhook support. It enables users to dynamically create custom MCP servers, manage recurring AI jobs, and track execution history with token and cost analytics.