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MCP Shrimp Task Manager

@cjo4m06

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基本情報

カテゴリ

生産性

ライセンス

MIT

トランスポート

stdio

作者

cjo4m06

MCP Shrimp Task Manager について

Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning A

#task-manager#programming#ai-assistant

MCP Shrimp Task Manager の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

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MCP Shrimp Task Manager のツール

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ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Shrimp Task Manager?

MCP Shrimp Task Manager is an MCP (Model Context Protocol) server that provides intelligent task management for AI-powered development. It helps break down complex projects into manageable tasks, maintains context across sessions, and is designed for developers using MCP-compatible AI clients like Claude Code.

How to use MCP Shrimp Task Manager?

Install Node.js 18+, clone the repository, then run npm install and npm run build. Configure the server by creating a .mcp.json file with the path to the built dist/index.js and setting the DATA_DIR environment variable. Start your AI client with the custom MCP config, then use commands like "init project rules", "plan task", "execute task", or "continuous mode".

Key features of MCP Shrimp Task Manager

  • Persistent memory across AI sessions
  • Structured workflows for planning and execution
  • Smart decomposition of complex tasks
  • Automatic dependency tracking between tasks
  • Research mode for systematic exploration
  • Optional web GUI and task viewer

Use cases of MCP Shrimp Task Manager

  • Feature development: plan and implement new functionality step by step
  • Bug fixing: research issues and execute fix tasks in continuous mode
  • Research and learning: systematically compare technologies or approaches

よくある質問

1

What are the runtime requirements?

Node.js 18+ with npm or yarn, and an MCP-compatible AI client such as Claude Code.

2

Where does task data live?

Task data is stored in the directory specified by the `DATA_DIR` environment variable in your configuration.

3

What transport does the server use?

The server communicates via MCP stdio transport, launched with a `node` command pointing to `dist/index.js`.

4

Is authentication supported?

No authentication mechanisms are mentioned in the documentation.

5

Is there a graphical interface?

Yes, an optional web GUI can be enabled by setting `ENABLE_GUI=true` in the configuration, and a separate React-based Task Viewer is available in the `tools/task-viewer` directory.

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