AI Coding Agents · cjo4m06

mcp-shrimp-task-manager

Shrimp Task Manager is an MCP server that helps AI agents break down complex development projects into structured, manageable tasks with persistent memory across sessions. It integrates with AI coding tools like Claude Code, Cline, and Cursor to enable systematic planning, execution, and reflection for software development workflows.

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Source: GitHub — github.com/cjo4m06/mcp-shrimp-task-manager

2.1k

GitHub stars

252

Forks

JavaScript

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	cjo4m06/mcp-shrimp-task-manager
Owner	cjo4m06
Primary language	JavaScript
License	MIT — OSI-approved
Stars	2.1k
Forks	252
Open issues	41
Latest release	Unknown
Last updated	2025-08-21
Source	https://github.com/cjo4m06/mcp-shrimp-task-manager

What mcp-shrimp-task-manager is

A JavaScript-based MCP (Model Context Protocol) server implementing task decomposition, dependency tracking, and persistent storage for AI-assisted development. It provides structured tools for task planning, execution, research mode, and agent-based task assignment, with optional React-based task viewer and lightweight web GUI interfaces.

Quickstart

Get the mcp-shrimp-task-manager source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/cjo4m06/mcp-shrimp-task-manager.git2cd mcp-shrimp-task-manager3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

AI-Assisted Feature Development

Use Shrimp to have AI agents systematically plan and implement complex features (e.g., user authentication, API endpoints) by breaking them into subtasks with tracked dependencies, maintaining context across multiple agent interactions.

Persistent Task State in Token-Limited Environments

Leverage Shrimp's persistent memory and structured storage to maintain task context and progress across separate AI sessions, avoiding context loss when working with token limits or resuming work days later.

Research and Architecture Planning

Use research mode to systematically explore technology choices and design decisions, then automatically convert findings into concrete task plans with dependencies before execution begins.

Implementation considerations

Requires MCP-compatible AI client (Claude Code, Cline, Claude Desktop, Cursor) and configuration via `.mcp.json` or native settings; not usable standalone.
Data directory (`DATA_DIR` env var) must be manually configured and accessible to Node.js process; no built-in migration or backup tooling documented.
Build step required (`npm run build`); relies on distributed `/dist` folder. Verify dist is committed or rebuild after clone.
Multiple language templates available (en, de, es, fr, it, hi, ko, pt, ru, zh) via `TEMPLATES_USE` env var; verify templates match your coding standards before adoption.
Task Viewer web UI (React-based) is optional but requires separate `npm install` and `npm run start:all` in `tools/task-viewer/`; adds complexity if needed.

When to avoid it — and what to weigh

Standalone Task Management without AI Integration — Shrimp is optimized for AI agent workflows and MCP clients. If you need a standalone team task manager or Jira replacement for human teams, traditional project management tools are better suited.
Minimal Node.js/JavaScript Skill on Team — Setup requires Node.js 18+, npm/yarn, MCP client configuration, and understanding of MCP protocol. Teams without JavaScript comfort may face deployment and troubleshooting friction.
Real-Time Multi-User Collaboration — No indication of multi-user locking, conflict resolution, or real-time sync. Designed for single-agent workflows; concurrent user access not clearly supported.
Heavily Regulated Environments without Security Review — No security audit, SOC 2, or compliance certification mentioned. Data is stored locally in configurable directories; sensitive code/tasks in regulated industries require independent security assessment.

License & commercial use

MIT License. Permissive OSI-approved license allowing commercial use, modification, and distribution with no warranty.

MIT license permits commercial use without restriction. However, no commercial support, SLA, or liability framework documented. Use in production requires internal risk assessment and testing; vendor assumes no responsibility for data loss or security issues.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

Local file-based storage with configurable `DATA_DIR`; no encryption at rest documented. No authentication or access control within the server itself. AI client responsible for prompt security and data sanitization. No security audit, vulnerability disclosure policy, or threat model provided. Data stored unencrypted on disk accessible to Node.js process. Teams handling sensitive code should review data storage practices and isolate `DATA_DIR` directory permissions.

Alternatives to consider

Continue / Refact (VS Code AI extensions)

Integrated coding assistants with built-in task/context management; no separate MCP server setup. Better for developers already in VS Code; less control over task structure.

GitHub Copilot + GitHub Projects

Tighter GitHub integration, multi-user support, public/enterprise SLA, and established security/compliance. Heavier for single-developer workflows; less customizable task reasoning.

Cursor IDE native task management

Native IDE task support without MCP configuration. Simpler UX for Cursor users; less portable and no persistent cross-session state documented.

Software development agency

Build on mcp-shrimp-task-manager with DEV.co software developers

Shrimp Task Manager integrates with your favorite AI coding tools to organize complex projects systematically. Evaluate it in a test project to see task decomposition and persistent context in action.

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Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

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Related on DEV.co

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mcp-shrimp-task-manager FAQ

Does Shrimp store my code or task data on external servers?

No. All data is stored locally in the `DATA_DIR` directory configured via environment variables. No cloud sync or external service integrations mentioned. Data remains on your machine.

Can multiple developers work on the same Shrimp task database?

Not clearly documented. Shrimp appears designed for single-agent (AI) workflows with local file storage. No locking, conflict resolution, or multi-user collaboration features evident. Concurrent access risks data corruption.

What AI clients does Shrimp support?

Primary support documented for Claude Code, Claude Desktop, and Cline (VS Code). Cursor is mentioned in topics but setup not detailed. Any MCP-compatible client theoretically works; verify maturity with your tool.

Is there a release/version history?

No formal releases published on GitHub. Project uses main branch for development. Current version is bleeding-edge. Risk: no stable versions to pin; breaking changes possible between pulls.

Software development & web development with DEV.co

From first prototype to production, DEV.co delivers software development services around tools like mcp-shrimp-task-manager. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across ai coding agents and beyond.

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