TaskMateAI

AI/MCP TODO task management application

TaskMateAI is a simple task management application that enables AI to autonomously manage and execute tasks, and can be operated through MCP (Model Context Protocol).

README available here

Related MCP server: Backlog Manager MCP Server

Features

Creating and managing tasks through MCP
Subtask Support
Priority-based task handling
Task progress management and reporting function
Add notes feature
Data persistence via JSON files
Task management for multiple AIs by agent ID
Organizing tasks by project

install

Prerequisites

Python 3.12 or higher
uv (Python package manager)
WSL (Windows Subsystem for Linux) *For Windows environments

Installation Instructions

Clone or download the repository:

git clone https://github.com/YourUsername/TaskMateAI.git cd TaskMateAI

Install the required packages:

uv install -r requirements.txt

How to use

Application launch

In the WSL environment you can run your application like this:

cd /path/to/TaskMateAI/src/TaskMateAI uv run TaskMateAI

MCP Configuration

Example of configuration for use with MCP:

{ "mcpServers": { "TodoApplication": { "command": "uv", "args": [ "--directory", "/絶対パス/TaskMateAI", "run", "TaskMateAI" ], "env": {}, "alwaysAllow": [ "get_tasks", "get_next_task", "create_task", "update_progress", "complete_task", "add_subtask", "update_subtask", "add_note", "list_agents", "list_projects" ], "defaultArguments": { "agent_id": "agent_123", "project_name": "" } } } }

{ "mcpServers": { "TodoApplication": { "command": "wsl.exe", "args": [ "-e", "bash", "-c", "cd /絶対パス/TaskMateAI && /home/ユーザー/.local/bin/uv run TaskMateAI" ], "env": {}, "alwaysAllow": [ "get_tasks", "get_next_task", "create_task", "update_progress", "complete_task", "add_subtask", "update_subtask", "add_note", "list_agents", "list_projects" ], "defaultArguments": { "agent_id": "agent_123", "project_name": "" } } } }

Available MCP Tools

TaskMateAI provides the following MCP tools:

get_tasks - Get a list of tasks (can be filtered by status and priority)
get_next_task - Get the next high priority task (automatically updates to in progress status)
create_task - Create a new task (with subtasks)
update_progress - Updates the progress of a task
complete_task - Mark a task as complete
add_subtask - Add a subtask to an existing task
update_subtask - Update the status of a subtask
add_note - Add a note to a task
list_agents - Get a list of available agent IDs
list_projects - Get a list of projects related to a specific agent

Data Format

Tasks are managed using the following structure:

{ "id": 1, "title": "タスクのタイトル", "description": "タスクの詳細な説明", "priority": 3, "status": "todo", // "todo", "in_progress", "done" のいずれか "progress": 0, // 0-100 の進捗率 "subtasks": [ { "id": 1, "description": "サブタスクの説明", "status": "todo" // "todo", "in_progress", "done" のいずれか } ], "notes": [ { "id": 1, "content": "ノートの内容", "timestamp": "2025-02-28T09:22:53.532808" } ] }

Data Storage

Task data is stored in a hierarchical structure:

output/ ├── tasks.json # デフォルトのタスクファイル ├── agent1/ │ ├── tasks.json # agent1のタスクファイル │ ├── project1/ │ │ └── tasks.json # agent1のproject1のタスクファイル │ └── project2/ │ └── tasks.json # agent1のproject2のタスクファイル └── agent2/ ├── tasks.json # agent2のタスクファイル └── projectA/ └── tasks.json # agent2のprojectAのタスクファイル

Each task file is automatically generated and updated when the application is run.

Managing agents and projects

To manage tasks for a specific agent or project, you can:

Specify a default agent in your MCP settings : By specifying agent_id in defaultArguments , it will be used automatically in all requests.
Specify projects in AI conversations : You can specify projects in the conversation, such as "Add a new task to project X."
Directly specified by AI : You can include agent_id and project_name in the request parameters.

Project Structure

TaskMateAI/ ├── src/ │ └── TaskMateAI/ │ ├── __init__.py # パッケージ初期化 │ └── __main__.py # メインアプリケーションコード ├── output/ # データ保存ディレクトリ │ └── tasks.json # タスクデータ (自動生成) ├── tests/ # テストコード │ ├── unit/ # ユニットテスト │ └── integration/ # 統合テスト ├── requirements.txt # 依存パッケージリスト └── README.md # このファイル

test

TaskMateAI provides a comprehensive test suite to ensure functionality reliability.

Test Configuration

The tests are organized in the following directory structure:

tests/ ├── __init__.py # テストパッケージの初期化 ├── conftest.py # テスト用フィクスチャの定義 ├── unit/ # ユニットテスト │ ├── __init__.py │ ├── test_task_utils.py # タスク関連ユーティリティのテスト │ ├── test_mcp_tools.py # MCPツール機能のテスト │ └── test_agent_projects.py # エージェントとプロジェクト管理のテスト └── integration/ # 統合テスト └── __init__.py

Test types

Unit testing : Ensures that individual components of an application function correctly
- test_task_utils.py : Tests basic functions such as reading and writing tasks, and generating IDs.
- test_mcp_tools.py : Tests the functionality of MCP tools (creating, updating, completing tasks, etc.)
- test_agent_projects.py : Tests agent ID and project management functionality
Integration testing : Ensure that multiple components work together correctly (future expansion planned)

How to run the test

You can run the test using the following command:

Run all tests:

cd /path/to/TaskMateAI uv run python -m pytest -xvs

Run a specific test file:

uv run python -m pytest -xvs tests/unit/test_task_utils.py

Run a specific test class:

uv run python -m pytest -xvs tests/unit/test_mcp_tools.py::TestMCPTools

Run a specific test function:

uv run python -m pytest -xvs tests/unit/test_task_utils.py::TestTaskUtils::test_read_tasks_with_data

Explanation of test arguments:

-x : Stops testing when an error occurs
-v : Display verbose output
-s : Display standard output during testing

Items to be fixed

Implementing the task template function
Building a dependency management system between tasks
Addition of schedule function
Introducing a tag-based task classification system
Implementing milestone management function

license

MIT

author

New AI Tees

TaskMateAI

TaskMateAI

AI/MCP TODO task management application

Features

install

Prerequisites

Installation Instructions

How to use

Application launch

MCP Configuration

Available MCP Tools

Data Format

Data Storage

Managing agents and projects

Project Structure

test

Test Configuration

Test types

How to run the test

Items to be fixed

license

author

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