MCP Shrimp Task Manager

@cjo4m06

Basic information

About MCP Shrimp Task Manager

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 config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

MCP Shrimp Task Manager tools

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.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

Frequently asked questions

What are the runtime requirements?

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

Where does task data live?

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

What transport does the server use?

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

Is authentication supported?

No authentication mechanisms are mentioned in the documentation.

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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