What can you do with this server?

The Taskwarrior MCP Server enables AI assistants to fully manage tasks using the Taskwarrior command-line tool, covering everything from basic operations to intelligent productivity analysis. Core Task Operations: * List tasks — Filter by status, project, tags, due dates, urgency, or custom Taskwarrior expressions * Add tasks — Create tasks with description, project, priority (H/M/L), due date, tags, and dependencies * Modify tasks — Update any attribute including description, project, priority, due date, and tags * Complete / Delete tasks — Mark tasks done or remove them (deletions are recoverable via undo) * Get task details — View all attributes and annotations for a specific task * Annotate tasks — Add notes or comments to a task * Start / Stop tasks — Track active work by marking tasks in-progress or paused * Undo — Revert the last operation Organization & Overview: * List projects and tags with task/usage counts * Task summary statistics — Pending task counts broken down by project, priority, and urgency Agent Intelligence Features: * Smart task recommendations with scoring and reasoning * Identify ready-to-work tasks (no pending dependencies) * Find blocked tasks and analyze dependency bottlenecks * Triage stale/forgotten tasks that need attention Output Formats: Most tools support both Markdown (human-readable) and JSON (machine-readable) output.

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
Agent Intelligence: Smart suggestions, dependency analysis, triage tools

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 .

Verifying Installation

# Check the version python -c "from taskwarrior_mcp import __version__; print(__version__)" # Or run the server directly taskwarrior-mcp --help

Configuration

See the examples/ directory for complete configuration files.

Claude Desktop

Add to your Claude Desktop configuration file:

Platform	Location
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"] } } }

Advanced Configuration

Use environment variables to customize Taskwarrior behavior:

{ "mcpServers": { "taskwarrior": { "command": "taskwarrior-mcp", "env": { "TASKRC": "/path/to/custom/.taskrc", "TASKDATA": "/path/to/custom/.task" } } } }

See examples/ for more configurations including multiple databases.

Available Tools

Core Task Management

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_bulk_get`	Get detailed info about multiple tasks at once
`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_project_summary`	Get detailed project summaries with priority breakdown, due dates, and active tasks
`taskwarrior_tags`	List all tags
`taskwarrior_undo`	Undo the last operation
`taskwarrior_summary`	Get task statistics

Agent Intelligence Tools

Tool	Description
`taskwarrior_suggest`	Get smart task recommendations with scoring and reasoning
`taskwarrior_ready`	List tasks that are ready to work on (no pending dependencies)
`taskwarrior_blocked`	List tasks that are blocked by dependencies
`taskwarrior_dependencies`	Analyze dependency graphs and find bottlenecks
`taskwarrior_triage`	Find forgotten/stale tasks that need attention
`taskwarrior_context`	Get rich task context with computed insights

Usage Examples

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

Basic Task Management

"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?"

Agent Intelligence

"What should I work on next?" - Uses taskwarrior_suggest for smart recommendations
"What tasks are ready to start?" - Uses taskwarrior_ready for unblocked tasks
"What's blocking my progress?" - Uses taskwarrior_blocked and taskwarrior_dependencies
"Any tasks I've forgotten about?" - Uses taskwarrior_triage for stale/orphaned tasks
"Give me context on task 5" - Uses taskwarrior_context for rich task details

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 see CONTRIBUTING.md for guidelines on:

Development setup
Commit message conventions (Conventional Commits)
Pull request process
Code style requirements

Install Server

A

security – no known vulnerabilities

A

license - permissive license

A

quality - confirmed to work

How are these scores calculated?

Resources

GitHub Repository

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Taskwarrior MCP Server

Taskwarrior MCP Server

Features

Prerequisites

Installing Taskwarrior

Installation

From PyPI (recommended)

From Source

Verifying Installation

Configuration

Claude Desktop

Claude Code CLI

Using uvx (no installation required)

Advanced Configuration

Available Tools

Core Task Management

Agent Intelligence Tools

Usage Examples

Basic Task Management

Agent Intelligence

Development

Setup

Running Tests

Code Quality

License

Contributing

Resources

Tools

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