How do I use Taskwarrior MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Taskwarrior MCP Server list all tasks in my Work project that are due this week" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Taskwarrior MCP Server

An MCP (Model Context Protocol) server that enables AI assistants to interact with Taskwarrior, the powerful command-line task management tool.

Features

Full Taskwarrior Integration: List, create, modify, complete, and delete tasks
Project & Tag Management: Organize tasks with projects and tags
Annotations: Add notes and context to tasks
Filtering: Use Taskwarrior's powerful filter expressions
Multiple Output Formats: Get responses in Markdown or JSON

Prerequisites

Python 3.10 or higher
Taskwarrior installed and available in your PATH

Installing Taskwarrior

# macOS brew install task # Ubuntu/Debian sudo apt install taskwarrior # Fedora sudo dnf install task # Arch Linux sudo pacman -S task

Installation

From PyPI (recommended)

pip install taskwarrior-mcp

From Source

git clone https://github.com/yourusername/taskwarrior-mcp.git cd taskwarrior-mcp pip install -e .

Configuration

Claude Desktop

Add to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{ "mcpServers": { "taskwarrior": { "command": "taskwarrior-mcp" } } }

Claude Code CLI

Add to your ~/.claude/settings.json:

{ "mcpServers": { "taskwarrior": { "command": "taskwarrior-mcp" } } }

Using uvx (no installation required)

{ "mcpServers": { "taskwarrior": { "command": "uvx", "args": ["taskwarrior-mcp"] } } }

Available Tools

Tool	Description
`taskwarrior_list`	List tasks with optional filtering
`taskwarrior_add`	Create a new task
`taskwarrior_complete`	Mark a task as completed
`taskwarrior_modify`	Modify task attributes
`taskwarrior_delete`	Delete a task
`taskwarrior_get`	Get detailed info about a task
`taskwarrior_annotate`	Add a note to a task
`taskwarrior_start`	Start working on a task
`taskwarrior_stop`	Stop working on a task
`taskwarrior_projects`	List all projects
`taskwarrior_tags`	List all tags
`taskwarrior_undo`	Undo the last operation
`taskwarrior_summary`	Get task statistics

Usage Examples

Once configured, you can interact with Taskwarrior through your AI assistant:

"What tasks do I have?"
"Add a task to review the quarterly report with high priority"
"Show me all tasks in the work project"
"Complete task 5"
"What's due this week?"

Development

Setup

git clone https://github.com/yourusername/taskwarrior-mcp.git cd taskwarrior-mcp python -m venv .venv source .venv/bin/activate pip install -e ".[dev]"

Running Tests

pytest

Code Quality

# Format code black . ruff check --fix . # Type checking mypy taskwarrior_mcp.py

License

MIT License - see LICENSE for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

This server cannot be installed

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security - not tested

A

license - permissive license

-

quality - not tested

How are these scores calculated?

Resources

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Taskwarrior MCP Server

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Features

Prerequisites

Installing Taskwarrior

Installation

From PyPI (recommended)

From Source

Configuration

Claude Desktop

Claude Code CLI

Using uvx (no installation required)

Available Tools

Usage Examples

Development

Setup

Running Tests

Code Quality

License

Contributing

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