mcpField
M
MCP Shrimp Task Manager

MCP Shrimp Task Manager

Local
cjo4m06.github.ioProductivity2.1kUpdated 62w ago

About MCP Shrimp Task Manager

Shrimp Task Manager is an MCP server that turns natural language requests into structured development tasks with dependency tracking. It targets AI agents and developers who need context kept across sessions, and emphasizes reflection and style consistency.

Key features

  1. 01Natural language to structured dev tasks
  2. 02Task dependency tracking
  3. 03Iterative task reflection and refinement
  4. 04Persistent task memory across sessions
  5. 05Project rules and coding standards
  6. 06Optional task viewer and web GUI

Use cases

  1. 01Breaking a large feature into executable subtasks
  2. 02Resuming development progress across multiple sessions
  3. 03Running a set of fix tasks in sequence

MCP support

This is an MCP server that exposes task planning, execution and listing commands to MCP clients such as Claude Code, Cline and Claude Desktop.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

🇺🇸 English | 🇩🇪 Deutsch | 🇪🇸 Español | 🇫🇷 Français | 🇮🇹 Italiano | 🇮🇳 हिन्दी | 🇰🇷 한국어 | 🇧🇷 Português | 🇷🇺 Русский | 🇨🇳 中文

MCP Shrimp Task Manager

🦐 Intelligent task management for AI-powered development - Break down complex projects into manageable tasks, maintain context across sessions, and accelerate your development workflow.

🚀 Quick Start

Prerequisites
  • Node.js 18+
  • npm or yarn
  • MCP-compatible AI client (Claude Code, etc.)
Installation
Installing Claude Code

Windows 11 (with WSL2):

# First, ensure WSL2 is installed (in PowerShell as Administrator)
wsl --install

# Enter Ubuntu/WSL environment
wsl -d Ubuntu

# Install Claude Code globally
npm install -g @anthropic-ai/claude-code

# Start Claude Code
claude

macOS/Linux:

# Install Claude Code globally
npm install -g @anthropic-ai/claude-code

# Start Claude Code
claude
Installing Shrimp Task Manager
# Clone the repository
git clone https://github.com/cjo4m06/mcp-shrimp-task-manager.git
cd mcp-shrimp-task-manager

# Install dependencies
npm install

# Build the project
npm run build
Configure Claude Code

Create a .mcp.json file in your project directory:

{
  "mcpServers": {
    "shrimp-task-manager": {
      "command": "node",
      "args": ["/path/to/mcp-shrimp-task-manager/dist/index.js"],
      "env": {
        "DATA_DIR": "/path/to/your/shrimp_data",
        "TEMPLATES_USE": "en",
        "ENABLE_GUI": "false"
      }
    }
  }
}

Example configuration:

{
  "mcpServers": {
    "shrimp-task-manager": {
      "command": "node",
      "args": ["/home/fire/claude/mcp-shrimp-task-manager/dist/index.js"],
      "env": {
        "DATA_DIR": "/home/fire/claude/project/shrimp_data",
        "TEMPLATES_USE": "en",
        "ENABLE_GUI": "false"
      }
    }
  }
}

Then start Claude Code with your custom MCP configuration:

claude --dangerously-skip-permissions --mcp-config .mcp.json
Other AI Clients

Cline (VS Code Extension): A VS Code extension for AI-assisted coding. Add to VS Code settings.json under cline.mcpServers

Claude Desktop: Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

Start Using
  1. Initialize your project: "init project rules"
  2. Plan a task: "plan task: implement user authentication"
  3. Execute tasks: "execute task" or "continuous mode"

💡 What is Shrimp?

Shrimp Task Manager is an MCP (Model Context Protocol) server that transforms how AI agents approach software development. Instead of losing context or repeating work, Shrimp provides:

  • 🧠 Persistent Memory: Tasks and progress persist across sessions
  • 📋 Structured Workflows: Guided processes for planning, execution, and verification
  • 🔄 Smart Decomposition: Automatically breaks complex tasks into manageable subtasks
  • 🎯 Context Preservation: Never lose your place, even with token limits

✨ Core Features

Task Management
  • Intelligent Planning: Deep analysis of requirements before implementation
  • Task Decomposition: Break down large projects into atomic, testable units
  • Dependency Tracking: Automatic management of task relationships
  • Progress Monitoring: Real-time status tracking and updates
Advanced Capabilities
  • 🔬 Research Mode: Systematic exploration of technologies and solutions
  • 🤖 Agent System: Assign specialized AI agents to specific tasks (Learn more)
  • 📏 Project Rules: Define and maintain coding standards across your project
  • 💾 Task Memory: Automatic backup and restoration of task history
Web Interfaces
🖥️ Task Viewer

Modern React interface for visual task management with drag-and-drop, real-time search, and multi-profile support.

Quick Setup:

cd tools/task-viewer
npm install
npm run start:all
# Access at http://localhost:5173

📖 Full Task Viewer Documentation

Task Viewer Interface

🌐 Web GUI

Optional lightweight web interface for quick task overview.

Enable in .env: ENABLE_GUI=true

📚 Documentation

🎯 Common Use Cases

Feature Development
Agent: "plan task: add user authentication with JWT"
# Agent analyzes codebase, creates subtasks

Agent: "execute task"
# Implements authentication step by step
Bug Fixing
Agent: "plan task: fix memory leak in data processing"
# Agent researches issue, creates fix plan

Agent: "continuous mode"
# Executes all fix tasks automatically
Research & Learning
Agent: "research: compare React vs Vue for this project"
# Systematic analysis with pros/cons

Agent: "plan task: migrate component to chosen framework"
# Creates migration plan based on research

🛠️ Configuration

Environment Variables

Create a .env file:

# Required
DATA_DIR=/path/to/data/storage

# Optional
ENABLE_GUI=true          # Enable web GUI
WEB_PORT=3000           # Custom web port
PROMPT_LANGUAGE=en      # Prompt language (en, zh, etc.)
Available Commands
CommandDescription
init project rulesInitialize project standards
plan task [description]Create a task plan
execute task [id]Execute specific task
continuous modeExecute all tasks sequentially
list tasksShow all tasks
research [topic]Enter research mode
reflect task [id]Review and improve task

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🌟 Credits

Created by cjo4m06 and maintained by the community.


GitHub • Issues • Discussions

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.