Dida MCP Server

Dida MCP Server

The Dida MCP Server bridges AI assistants with the TickTick/Dida365 task management ecosystem through the Model Context Protocol. By exposing a rich set of tools that map directly onto TickTick’s API, it allows conversational agents to create, update, organize, and batch‑process tasks as if they were native collaborators. This eliminates the need for developers to write custom integrations or maintain separate authentication flows, enabling AI assistants to act as powerful productivity companions.

At its core, the server implements OAuth‑based authentication for TickTick’s open API while also supporting a legacy username/password flow. Once authenticated, the server caches project and tag data to reduce round‑trips, delivering near real‑time responses. The toolset includes full CRUD operations for tasks and projects, task movement across projects or tags, and a dedicated batch endpoint that lets an assistant apply bulk changes—ideal for cleaning up inboxes or re‑prioritizing work streams.

A standout feature is the built‑in GTD (Getting Things Done) prompt. The server ships with a system message that guides the assistant to apply GTD principles when organizing tasks, ensuring consistent, methodical handling of incoming work. This is particularly valuable for developers who want to embed proven productivity frameworks into their AI workflows without writing additional logic.

Developers can integrate the server into any MCP‑compatible client. Once started, it automatically reads a configuration file containing OAuth tokens and project identifiers, then exposes the MCP endpoints. From there, an assistant can fetch a list of tasks, add new items to specific projects, move tasks between contexts, or apply tags—all while the server handles authentication and rate limiting transparently.

Real‑world scenarios include: a virtual assistant that scans emails, extracts action items, and creates tasks in the user’s “Inbox” project; a team bot that aggregates daily stand‑up notes into a shared project and tags them for follow‑up; or a personal productivity app that synchronizes reminders across devices while the AI suggests priority adjustments based on upcoming deadlines. By offloading task‑management logic to a dedicated MCP server, developers free up their own codebases for higher‑level reasoning and user experience design.