LibreAI / KI-Agenten / mcp-shrimp-task-manager

// agents · cjo4m06/mcp-shrimp-task-manager

mcp-shrimp-task-manager

mcp-shrimp-task-manager ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von cjo4m06 (cjo4m06/mcp-shrimp-task-manager auf GitHub). Es hat 2.147 Sterne auf GitHub und 254 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 21. August 2025 auf GitHub aktualisiert.

Shrimp Task Manager: an MCP server that turns natural language into structured, dependent dev tasks.

★ 2,1 Tsd. Sterne⑂ 254 ForksMITaktualisiert Aug 2025

Auf GitHub ansehen ↗Official site ↗

▦ Visual — das README dieses Projekts enthält keinen einbettbaren Screenshot,
darum hier ein Platzhalter. Die Anleitung unten ist trotzdem vollständig.

// projektdaten

Projektdaten

Repository: cjo4m06/mcp-shrimp-task-manager
GitHub-Sterne: 2.147
Forks: 254
Lizenz: MIT
Zuletzt auf GitHub aktualisiert: 21. August 2025
Kategorie: KI-Agenten
Eintragstyp: Vollständige Installationsanleitung
Offizielle Website: Official site

// so funktioniert es

So funktioniert es

Clarify your goal
Decide which project you want an agent to plan and execute in structured steps rather than ad hoc prompts.
Get the project
Clone the repository, install dependencies, and build the project to produce the server entry point.
Install and configure
Add the shrimp-task-manager entry to your MCP client's configuration with a data directory and template language, then start the client with that config.
Run your first task
Initialise project rules, plan your first task in natural language, and execute tasks one by one or in continuous mode.

// funktionen

Warum es so beliebt ist

Intelligent task planning and decomposition

Analyses requirements and breaks complex projects into atomic, testable subtasks automatically.

Dependency tracking and progress monitoring

Manages relationships between tasks and tracks status in real time as work proceeds.

Persistent memory across sessions

Tasks, progress, and history are stored and backed up, so agents keep context despite token limits or new sessions.

Research mode and project rules

A systematic research mode explores technologies, and project rules keep coding standards consistent across tasks.

Specialised agent assignment

Different AI agents can be assigned to specific tasks, with reflection steps to review and improve completed work.

Task viewer and optional web GUI

A React task viewer with drag-and-drop and search, plus a lightweight web GUI enabled through configuration.

// selbst ausführen

Führe es selbst aus

Clone, install, and build

Node.js 18 or newer is required.

git clone https://github.com/cjo4m06/mcp-shrimp-task-manager.git
cd mcp-shrimp-task-manager
npm install && npm run build

Configure your MCP client

Add the server to a .mcp.json in your project with your data directory, as shown in the README.

# .mcp.json: command "node", args ["/path/to/mcp-shrimp-task-manager/dist/index.js"], env DATA_DIR, TEMPLATES_USE=en, ENABLE_GUI=false

Start planning
Launch your client with the config and use the natural-language commands.
```
claude --mcp-config .mcp.json
# then ask: plan task: implement user authentication
```

// anwendungsfälle

Was du damit bauen kannst

Breaking a large feature into dependent subtasks an agent can execute reliably
Keeping task context alive across many short agent sessions
Researching a technology choice systematically before committing to a migration plan
Tracking progress of agent-driven bug fixing with a visual task board

// häufige fragen

Häufige Fragen

Who maintains it?

It was created by cjo4m06 and is maintained with community contributions on GitHub.

Is it free to use?

Yes, it is MIT-licensed and free; you use it through your existing MCP client and its model access.

Does it need a paid API key?

Shrimp itself needs no API key; the AI client you connect it to (such as Claude Code) uses your own account or key.

How does it compare to a well-known alternative?

A plain to-do list records tasks; Shrimp is an MCP server that actively plans, decomposes, orders by dependency, and reflects on tasks inside the agent's workflow.

How do I get started?

Clone the repo, npm install, npm run build, add the server entry to your client's MCP config, and ask it to plan a task.

// weiter entdecken

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Hol dir mcp-shrimp-task-manager

Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.

Auf GitHub ansehen ↗← Mehr Tools: KI-Agenten