LibreAI / AI Agents / mcp-shrimp-task-manager
// agents · cjo4m06/mcp-shrimp-task-manager

mcp-shrimp-task-manager

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

★ 2.1k stars⑂ 254 forksMITupdated 2025-08
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

mcp-shrimp-task-manager is an open-source ai agents project by cjo4m06 (cjo4m06/mcp-shrimp-task-manager on GitHub). It has 2,147 GitHub stars and 254 forks, is released under the MIT license, and was last updated on GitHub on 21 August 2025.

GitHub stars
2,147
Forks
254
License
MIT
Last updated on GitHub
21 August 2025
Category
AI Agents
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your goal

    Decide which project you want an agent to plan and execute in structured steps rather than ad hoc prompts.

  2. Get the project

    Clone the repository, install dependencies, and build the project to produce the server entry point.

  3. 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.

  4. Run your first task

    Initialise project rules, plan your first task in natural language, and execute tasks one by one or in continuous mode.

// features

Why people love it

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.

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// run it

Run it yourself

  1. 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
  2. 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
  3. 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
// use cases

What you can build

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// faq

Questions, answered

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.

// keep exploring

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// alternatives

Alternatives in AI Agents

The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if mcp-shrimp-task-manager is not the right fit.

Get mcp-shrimp-task-manager

Free and open — grab the source, star the repo, and start creating.