How does it differ from the Temp Notes MCP Server?
It is an evolution of Temp Notes that uses a structured JSON format instead of plain text, enabling checklists, context fields, metadata, and progress tracking.
@landicefu
基本情報
概要はまだありません
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"divide-and-conquer": {
"command": "npx",
"args": [
"-y",
"@landicefu/divide-and-conquer-mcp-server"
],
"disabled": false
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。
A Model Context Protocol (MCP) server that enables AI agents to break down complex tasks into manageable pieces using a structured JSON format. It is designed for AI agents facing context window limitations when working on multi-step or multi‑conversation tasks.
Add the server to your MCP configuration using npx -y @landicefu/divide-and-conquer-mcp-server, then invoke tools such as initialize_task, add_checklist_item, get_current_task_details, and get_checklist_summary via use_mcp_tool. The server stores task data locally in ~/.mcp_config/divide_and_conquer.json.
It is an evolution of Temp Notes that uses a structured JSON format instead of plain text, enabling checklists, context fields, metadata, and progress tracking.
On macOS/Linux at `~/.mcp_config/divide_and_conquer.json` and on Windows at `C:\Users\username\.mcp_config\divide_and_conquer.json`. The file is created automatically on first write.
It selectively provides full context only for the current (first uncompleted) task, while other tasks are returned with limited fields, saving context window space.
No, it runs locally as a Node.js process and requires no external APIs or databases.
It offers 14 tools including `initialize_task`, `add_checklist_item`, `mark_task_done`, `get_current_task_details`, `get_checklist_summary`, and more for managing tasks, checklists, notes, resources, and metadata.
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