Let MCP-compatible AI assistants read and write Apple Reminders.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "remindctl-mcp" yet — see the docs or source repo.
Create a task in Apple Reminders to remind me tomorrow at 3 PM to submit my weekly report.
The AI writes the reminder to Apple Reminders through this MCP tool and returns the creation result.
Read the tasks due today from my Apple Reminders and list them in time order.
The AI reads the relevant tasks from Apple Reminders and returns them as a clear list.
Change my 'Dentist appointment' reminder in Apple Reminders to next Tuesday at 10 AM.
The AI updates the existing reminder through the tool and reports whether the change succeeded.
Office workers or students can use natural language to ask an AI to create, view, or edit Apple Reminders, reducing manual input. It fits everyday task and reminder management.
Developers can connect an MCP-compatible AI assistant to Apple Reminders for reminder read/write access through a standard protocol. This is useful for adding task management capabilities to assistants.
This is an MCP server that accesses Apple Reminders via remindctl. It allows MCP-compatible AI assistants to read from and write to Apple Reminders.
Based on the description, it depends on remindctl and is used to connect to Apple Reminders. For more installation and runtime prerequisites, see the source repository.
It is not a standalone reminders app, but an MCP service layer for AI assistants. Its main value is letting MCP-capable models operate Apple Reminders through a standard protocol.
Manage Apple Reminders lists and tasks with add, edit, complete, and delete actions.
Let AI manage Apple Reminders by creating, listing, completing, and deleting tasks.
Manage macOS Reminders via MCP for automated task creation and updates.
Let AI manage Apple Reminders on macOS through create, read, list, and delete actions.
Let AI read and manage macOS Reminders and reminder lists.
Manage Apple Reminders with CRUD, natural-language dates, search, and list automation.