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Task Manager MCP Server

@tradesdontlie

代码仓库

基本信息

分类

生产力

许可证

MIT

传输方式

stdio

作者

tradesdontlie

关于 Task Manager MCP Server

A task management MCP server that provides comprehensive project and task tracking capabilities

Task Manager MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "task-manager-mcp": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-e",
        "."
      ]
    }
  }
}

Task Manager MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Task Manager MCP Server?

A template implementation of the Model Context Protocol (MCP) server for managing tasks and projects, providing task management, project organization, task tracking, and PRD parsing. It enables AI agents to manage tasks, track project progress, and break down Product Requirements Documents (PRDs) into actionable tasks. Serves as a practical template for building custom MCP servers with task management capabilities.

How to use Task Manager MCP Server?

Install using uv or Docker, configure environment variables in a .env file (including TRANSPORT, HOST, PORT), then run with python3 src/main.py or the Docker container. Use the provided tools (e.g., create_task_file, add_task, update_task_status, parse_prd) to manage projects and tasks programmatically.

Key features of Task Manager MCP Server

  • create_task_file, add_task, update_task_status, get_next_task for task management
  • parse_prd converts PRDs into structured tasks automatically
  • expand_task breaks tasks into smaller subtasks
  • estimate_task_complexity and get_task_dependencies for project planning
  • generate_task_file creates file templates from task descriptions
  • suggest_next_actions provides AI‑powered next‑step recommendations

Use cases of Task Manager MCP Server

  • Automatically decompose a Product Requirements Document into a structured task list
  • Track progress of tasks and subtasks within a project
  • Retrieve the next uncompleted task to maintain workflow focus
  • Estimate task complexity and time requirements for planning
  • Generate file templates based on task descriptions to speed up development

常见问题

1

What are the prerequisites to run the server?

Python 3.12+ is required, along with API keys for an LLM provider (OpenAI, OpenRouter, or Ollama). Docker is recommended but optional.

2

How do I configure the transport protocol?

Set the `TRANSPORT` environment variable to `sse` or `stdio`. For SSE, also set `HOST` and `PORT` (default `0.0.0.0:8050`).

3

How can I integrate this server with MCP clients?

Use the provided JSON configuration for either SSE (URL `http://localhost:8050/sse`) or stdio (command `python3 src/main.py` with environment variables).

4

Can I extend or customize the Task Manager MCP Server?

Yes. The template is designed to be extended—add custom tools with the `@mcp.tool()` decorator, implement project‑specific templates, or integrate with existing development tools.

5

Where are task data stored?

The README does not specify a storage backend; data persistence is not described.

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