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The Todoist alternative that's GTD-native and local-first

Done Bear is a Todoist alternative for people who want GTD built in instead of assembled from filters and labels. It's local-first, so every view loads instantly online or offline, with real-time team workspaces and a CLI, GraphQL API, and MCP server for AI assistants. Free to start.

Done Bear vs Todoist at a glance

Done Bear

Built-in 5-view GTD system
Local-first, instant loads
Web, macOS, Windows, Linux, iOS
Real-time team workspaces
CLI, GraphQL API, MCP server
Free to start, from $7/mo billed yearly

Todoist

Build it with filters + labels
Cloud-first with offline mode
Nearly everywhere
Shared projects
REST API, CLI, MCP server
Free tier, paid per user

Why people switch from Todoist

GTD should be the default, not a configuration

In Todoist, a GTD setup is a project you maintain: filters, labels, and conventions that drift over time. Done Bear ships the five GTD views as the product, so the system holds itself together.

Local-first means the app is never 'loading'

Done Bear renders from a local store first, so opening Today is instant on a plane, on the subway, or on hotel Wi-Fi. Sync happens in the background, not between you and your list.

Agent-ready out of the box

Done Bear's hosted MCP server lets Claude, ChatGPT, and other AI assistants act on your tasks with your permission (triage the inbox, plan the day, file follow-ups) through a supported, first-class interface.

Who should stay on Todoist

If you rely on Todoist's natural-language quick add across every platform it supports, its years of integrations, or its karma-style habits, it remains an excellent general-purpose to-do app. Done Bear is for people who specifically want GTD structure, local-first speed, and agent integrations.

Moving from Todoist

There's no one-click importer yet. Export your Todoist data as CSV to keep an archive, then recreate your structure in Done Bear: projects map to projects, labels to labels, and the GTD views organize the rest.

Browse the Done Bear docs

Frequently asked questions