The Divide and Conquer MCP server enables AI agents to break down complex tasks into manageable pieces using structured JSON storage. Developed by Landice Fu, it evolved from a simpler text-based approach to provide robust task tracking with checklist functionality, progress monitoring, and context preservation across multiple conversations. The implementation includes tools for initializing tasks, managing checklist items, tracking completion status, and retrieving task summaries, making it particularly valuable for complex software development projects, research activities, and project planning where context needs to be maintained across multiple interactions.
Creates a new task with the specified description and optional initial checklist items.
Updates the main task description.
Updates the context information for all tasks.
Adds a new item to the checklist.
Updates an existing checklist item.
Marks a checklist item as done.
Marks a checklist item as not done.
Removes a checklist item.
Moves a checklist item to a new position.
Adds a note to the task.
Adds a resource to the task.
Updates the task metadata.
Clears the current task data.
Returns a summary of the checklist with completion status. Context information is intentionally excluded from the summary to save context window space.
Retrieves details of the current task (first uncompleted task) with full context, along with all other tasks with limited fields.
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