Taskwarrior MCP Server
An MCP server that enables AI assistants to interact with the Taskwarrior command-line task management tool. It allows users to list, create, modify, and organize tasks using projects, tags, and annotations through natural language.
README
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.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.