TaskMateAI

# TaskMateAI ## AI/MCP TODO Task Management Application TaskMateAI is a simple task management application that allows AI to autonomously manage and execute tasks through MCP (Model Context Protocol). [日本語版 README はこちら](README.md) ## Features - Task creation and management through MCP - Subtask support - Priority-based task processing - Task progress management and reporting - Note-taking functionality - Data persistence via JSON files - Multiple agent management through agent IDs - Project-based task organization ## Installation ### Prerequisites - Python 3.12 or higher - uv (Python package manager) - WSL (Windows Subsystem for Linux) *for Windows environments ### Installation Steps 1. Clone or download the repository: ```bash git clone https://github.com/YourUsername/TaskMateAI.git cd TaskMateAI ``` 2. Install required packages: ```bash uv install -r requirements.txt ``` ## Usage ### Starting the Application In a WSL environment, you can run the application as follows: ```bash cd /path/to/TaskMateAI/src/TaskMateAI uv run TaskMateAI ``` ### MCP Configuration Example configuration for use with MCP: ```json { "mcpServers": { "TodoApplication": { "command": "uv", "args": [ "--directory", "/absolute/path/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": "" } } } } ``` ```json { "mcpServers": { "TodoApplication": { "command": "wsl.exe", "args": [ "-e", "bash", "-c", "cd /absolute/path/TaskMateAI && /home/user/.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: 1. **get_tasks** - Retrieve task list (filterable by status and priority) 2. **get_next_task** - Get the next highest priority task (automatically updates to in-progress status) 3. **create_task** - Create a new task (with subtasks) 4. **update_progress** - Update task progress 5. **complete_task** - Mark a task as complete 6. **add_subtask** - Add a subtask to an existing task 7. **update_subtask** - Update subtask status 8. **add_note** - Add a note to a task 9. **list_agents** - Get a list of available agent IDs 10. **list_projects** - Get a list of projects associated with a specific agent ### Data Format Tasks are managed with the following structure: ```json { "id": 1, "title": "Task title", "description": "Detailed task description", "priority": 3, "status": "todo", // one of "todo", "in_progress", "done" "progress": 0, // progress percentage 0-100 "subtasks": [ { "id": 1, "description": "Subtask description", "status": "todo" // one of "todo", "in_progress", "done" } ], "notes": [ { "id": 1, "content": "Note content", "timestamp": "2025-02-28T09:22:53.532808" } ] } ``` ## Data Storage Task data is stored in a hierarchical structure: ``` output/ ├── tasks.json # Default tasks file ├── agent1/ │ ├── tasks.json # Tasks for agent1 │ ├── project1/ │ │ └── tasks.json # Tasks for agent1's project1 │ └── project2/ │ └── tasks.json # Tasks for agent1's project2 └── agent2/ ├── tasks.json # Tasks for agent2 └── projectA/ └── tasks.json # Tasks for agent2's projectA ``` ## Project Structure ``` TaskMateAI/ ├── src/ │ └── TaskMateAI/ │ ├── __init__.py # Package initialization │ └── __main__.py # Main application code ├── output/ # Data storage directory │ └── tasks.json # Task data (auto-generated) ├── tests/ # Test code directory │ ├── unit/ # Unit tests │ └── integration/ # Integration tests ├── requirements.txt # Dependency package list └── README.md # This file ``` ## Testing TaskMateAI provides a comprehensive test suite to ensure reliability of all features. ### Test Structure Tests are organized in the following directory structure: ``` tests/ ├── __init__.py # Test package initialization ├── conftest.py # Test fixtures definition ├── unit/ # Unit tests │ ├── __init__.py │ ├── test_task_utils.py # Tests for task-related utilities │ ├── test_mcp_tools.py # Tests for MCP tool functionality │ └── test_agent_projects.py # Tests for agent and project management └── integration/ # Integration tests └── __init__.py ``` ### Types of Tests 1. **Unit Tests**: Verify that individual components of the application function correctly - `test_task_utils.py`: Tests basic functionality like task reading/writing and ID generation - `test_mcp_tools.py`: Tests MCP tool functionality (creating, updating, completing tasks, etc.) - `test_agent_projects.py`: Tests agent ID and project management features 2. **Integration Tests**: Verify that multiple components work correctly together (planned for future expansion) ### Running Tests You can run tests using the following commands: 1. Run all tests: ```bash cd /path/to/TaskMateAI uv run python -m pytest -xvs ``` 2. Run a specific test file: ```bash uv run python -m pytest -xvs tests/unit/test_task_utils.py ``` 3. Run a specific test class: ```bash uv run python -m pytest -xvs tests/unit/test_mcp_tools.py::TestMCPTools ``` 4. Run a specific test function: ```bash uv run python -m pytest -xvs tests/unit/test_task_utils.py::TestTaskUtils::test_read_tasks_with_data ``` Test argument explanation: - `-x`: Stop testing when an error occurs - `-v`: Show verbose output - `-s`: Show standard output during tests ## Planned Improvements - Add task template functionality - Implement task dependencies - Add scheduling features - Implement tagging system for tasks - Add milestone tracking ## License MIT ## Author [NewAITees](https://github.com/NewAITees)