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
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"divide-and-conquer": {
"command": "npx",
"args": [
"-y",
"@landicefu/divide-and-conquer-mcp-server"
],
"disabled": false
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
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.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,

A free remote MCP server for The Living Bread. Bible passages read word for word from a stored public domain text with an evidence label, keyword search and cross references, real churches, gatherings and prayer groups w
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
A curated list of references for MLOps
不止于 CSS
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