TickTick MCP Server

The TickTick MCP Server bridges the gap between AI assistants and the TickTick task‑management ecosystem, allowing developers to harness real‑time productivity data without writing custom API wrappers. By exposing a rich set of task, project, and subtask operations through the MCP interface, it empowers AI agents to create, modify, and query tasks directly within a user’s TickTick workspace. This eliminates the need for separate OAuth flows or SDKs, streamlining integration and reducing latency in AI‑driven workflows.

At its core, the server offers comprehensive task management: create, read, update, and delete tasks with full property support—including titles, descriptions, due dates, reminders, recurrence rules, priorities, and subtasks. It also provides project management primitives that let agents list all projects, retrieve individual project details, and fetch a project’s tasks and columns in one call. Subtask handling is fully supported, enabling nested task structures that mirror the native TickTick experience. Each operation is protected by OAuth 2, ensuring secure access while maintaining user privacy.

Key capabilities include:

• Full CRUD for tasks and projects with granular control over scheduling, reminders, and priorities.
• Subtask nesting that preserves completion status and timestamps.
• Batch project retrieval to quickly surface all active workspaces for a user.
• Error handling that surfaces clear messages for common pitfalls such as missing permissions or invalid identifiers.

Real‑world use cases are abundant. An AI assistant could schedule a meeting reminder, automatically add follow‑up tasks to the appropriate project, and mark them complete once the assistant confirms. In a team setting, the server can populate a shared project with tasks generated from meeting minutes, or pull all pending tasks to generate daily stand‑up summaries. Developers building productivity bots can leverage the server to sync external calendars, automate habit tracking, or create adaptive task lists based on user behavior.

Integration into AI workflows is straightforward: the MCP server’s tools are exposed as first‑class actions that can be invoked by prompts or programmatic calls. Because the server handles authentication, developers can focus on business logic while AI agents orchestrate complex task flows. The standout advantage is the end‑to‑end security model—OAuth 2 tokens are stored and refreshed behind the scenes, eliminating token leakage risks. Additionally, the server’s comprehensive error responses help AI agents diagnose issues in real time, leading to smoother user experiences.