DeltaTask - Advanced Task Management System

A powerful, locally-hosted task management application with Obsidian integration and a Model Context Protocol (MCP) server.

Features

• Smart Task Management: Create tasks with urgency levels and effort estimates

• Prioritization Engine: Automatically sorts tasks by urgency and effort

• Task Decomposition: Split larger tasks into manageable subtasks

• Tagging System: Organize tasks with custom tags

• Local Storage: All data stored locally in SQLite database

• Obsidian Integration: Bi-directional sync with Obsidian markdown files

• MCP Server: Full API access through Model Context Protocol

Related MCP server: TaskMateAI

Technical Details

Data Model

• Tasks: Core task entity with properties:

  • Title and description

  • Urgency (1-5 scale, 5 being highest)

  • Effort (1-21 scale, following Fibonacci sequence)

  • Completion status

  • Parent-child relationships for subtasks

  • Tags for categorization

Database Schema

The application uses SQLite with the following tables:

• todos: Stores all task items and their properties

• tags: Stores unique tag names

• todo_tags: Junction table for many-to-many relationship between tasks and tags

Obsidian Integration

DeltaTask creates and maintains a structured Obsidian vault:

• Task files with frontmatter metadata

• Tag-based views for filtering tasks

• Statistics dashboard

• Bi-directional sync between Obsidian markdown and SQLite database

MCP API Endpoints

The MCP server exposes the following operations:

• get_task_by_id: Get a specific task by ID

• search_tasks: Find tasks by title, description, or tags

• create_task: Create a new task

• update_task: Update a task's properties

• delete_task: Remove a task

• sync_tasks: Sync tasks from Obsidian markdown into SQLite

• list_tasks: List all tasks

• get_statistics: Retrieve metrics about tasks

• create_subtasks: Split a task into multiple subtasks

• get_all_tags: Get all unique tag names

• get_subtasks: Get subtasks for a given parent task

• finish_task: Mark a task as completed

Getting Started

Prerequisites

• Python 3.10+

• SQLite3

• Obsidian (optional, for markdown integration)

Installation

1. Clone this repository

2. Set up the Python environment using uv:

   # Create and activate the virtual environment uv venv source .venv/bin/activate # On Windows: .venv\Scripts\activate # Install dependencies uv pip install -r requirements.txt

Running the MCP Server

The DeltaTask MCP server can be used with Claude for Desktop:

1. Configure Claude for Desktop:

   • Open or create ~/Library/Application Support/Claude/claude_desktop_config.json

   • Add the DeltaTask server configuration:

   { "mcpServers": { "deltatask": { "command": "uv", "args": [ "--directory", "/ABSOLUTE/PATH/TO/DeltaTask", "run", "server.py" ] } } }

   • Restart Claude for Desktop

If you run into issues or want more details, check out the Docs for the MCP.

For instance from the docs:

You may need to put the full path to the uv executable in the command field. You can get this by running which uv on MacOS/Linux or where uv on Windows.

2. Use the DeltaTask tools in Claude for Desktop by clicking the hammer icon

Model Context Protocol (MCP)

This application implements a Model Context Protocol approach for task management:

1. Structured Data Model: Clearly defined schema for tasks with relationships

2. Priority Calculation: Intelligent sorting based on multiple factors

3. Hierarchical Organization: Parent-child relationships for task decomposition

4. Tagging System: Flexible categorization for better context

5. Statistics and Insights: Data aggregation for understanding task patterns

6. Obsidian Integration: Markdown-based visualization and editing

License

MIT License