apple-reminders-mcp
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Alternatives to apple-reminders-mcp
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Related Servers
- AlicenseNot gradedqualityCmaintenanceMCP server for Apple Reminders, enabling management of reminders and lists via tools like add, edit, complete, and delete reminders.MIT
- AlicenseNot gradedqualityDmaintenanceEnables fuzzy search, creation, and management of Apple Reminders via CLI or MCP tools.15 npmMIT
- AlicenseAqualityDmaintenanceEnables AI assistants to manage Apple Reminders lists and reminders on macOS, including creating, updating, completing, and deleting reminders.7297 npm5MIT
- AlicenseNot gradedqualityBmaintenanceEnables Codex on Windows to manage iPhone/iCloud Reminders through a local MCP bridge, including listing, creating, updating, completing, and deleting reminders with due dates, notes, and priorities.MIT
- AlicenseNot gradedqualityCmaintenanceA macOS-only MCP server that exposes Apple Reminders to AI clients, enabling create, read, update, delete, search, and organization of reminders and lists through natural language.1MIT
- FlicenseNot gradedqualityDmaintenanceA Model Context Protocol server providing comprehensive integration with Apple Reminders, enabling CRUD operations, natural language date parsing, advanced search, and list management.-
TDQS
Scored across 7 tools
Most tools are distinct, but complete_reminders overlaps with edit_reminder's complete/incomplete flags, and list_reminder_lists (which can show a list's contents) overlaps with show_reminders' list filter. The descriptions mitigate this somewhat but boundaries remain blurry.
Mostly verb_noun, but plurality is inconsistent (add_reminder vs show_reminders/complete_reminders/delete_reminders) and list_reminder_lists is an awkward verb_noun_noun construction. Still readable and mostly predictable.
Seven tools is well-scoped for a reminders domain, with each tool earning its place across create/read/edit/complete/delete/list-management operations.
Covers the full reminder lifecycle (add, show, edit, complete, delete) plus list management, leaving few gaps. Minor omissions like text search or batch reassignment are workable around via filters and edit.