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Task Manager MCP Server

@MustakAhmedcse

リポジトリ

基本情報

カテゴリ

生産性

トランスポート

stdio

作者

MustakAhmedcse

Task Manager MCP Server について

概要はまだありません

#task-manager#mcp-server#ai-assistant

Task Manager MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "to-do-app-mcp-server": {
      "command": "python",
      "args": [
        "server.py"
      ]
    }
  }
}

Task Manager MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Task Manager MCP Server?

Task Manager MCP Server is a task management tool that integrates with a database and uses LangChain for AI‑driven assistance. It provides APIs for adding, viewing, completing, and deleting tasks, and includes a Streamlit‑based user interface. This server is designed for developers and users who want to manage tasks programmatically or through a visual interface with AI support.

How to use Task Manager MCP Server?

Clone the repository, install dependencies with pip install -r requirements.txt, then start the MCP server by running python server.py. To use the graphical interface, run streamlit run streamlit.py. Debugging configurations are available in .vscode/launch.json.

Key features of Task Manager MCP Server

  • Add, list, complete, and remove tasks.
  • Streamlit‑based user interface for visual interaction.
  • LangChain integration for intelligent task management.
  • Tool‑based architecture connecting to external tools.
  • Structured project with separate modules for server, agent, and UI.

Use cases of Task Manager MCP Server

  • Rapidly build a task management application with a backend server.
  • Manage tasks through an AI agent that processes natural language queries.
  • Debug and test task operations using a Streamlit frontend.
  • Integrate task management into larger LangChain‑powered workflows.

よくある質問

1

What does the server do?

The server manages tasks using tools connected to a database. It provides APIs for adding, viewing, completing, and deleting tasks, and integrates with LangChain for AI‑driven task management.

2

How do I run the server and the UI?

Start the MCP server by running `python server.py`. For the graphical interface, run `streamlit run streamlit.py`.

3

What are the dependencies?

All dependencies are listed in `requirements.txt`. Install them with `pip install -r requirements.txt`.

4

What tools are available on the server?

The server provides four tools: `list_tasks` (list all tasks), `add_task` (add a new task), `remove_task` (remove a task by ID), and `mark_complete` (mark a task as complete).

5

How does the AI agent work?

The AI agent in `agent.py` uses LangChain to process user queries and interact with the task management tools, enabling intelligent responses and task operations.

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