TaskWarrior MCP Server
@awwaiid
About TaskWarrior MCP Server
MCP Server for TaskWarrior!
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"taskwarrior": {
"command": "npx",
"args": [
"-y",
"mcp-server-taskwarrior"
]
}
}
}Tools
3Get a list of all pending tasks
Add a new task to TaskWarrior
Mark a task as completed
Overview
What is TaskWarrior MCP Server?
Node.js server implementing Model Context Protocol for TaskWarrior operations, allowing AI assistants to interact with a local TaskWarrior installation via its task binary.
How to use TaskWarrior MCP Server?
Install globally with npm install -g mcp-server-taskwarrior, ensure TaskWarrior is installed and configured, then add the server to claude_desktop_config.json using npx -y mcp-server-taskwarrior. Use the provided tools to list, add, and complete tasks.
Key features of TaskWarrior MCP Server
- View pending tasks
- Filter tasks by project and tags
- Add new tasks with description, due date, priority, project, tags
- Mark tasks as complete
Use cases of TaskWarrior MCP Server
- Ask "What are my current work tasks?" to get a filtered task list
- Add a high-priority task like "Call my sister"
- Mark a task as done after completion
FAQ from TaskWarrior MCP Server
What does this server offer over using TaskWarrior directly?
It provides a Model Context Protocol interface so AI assistants can read, create, and complete tasks through natural language rather than direct command-line usage.
What runtime or dependencies are required?
Requires Node.js and a locally installed and configured TaskWarrior (the task binary) – the server calls this binary for all operations.
Where does task data live?
Task data stays in your local TaskWarrior database; the server does not sync or store data externally.
What are the known limitations?
The server currently uses the unstable task id instead of the more reliable UUID; TaskWarrior may renumber IDs when tasks are added or removed.
Frequently asked questions
What does this server offer over using TaskWarrior directly?
It provides a Model Context Protocol interface so AI assistants can read, create, and complete tasks through natural language rather than direct command-line usage.
What runtime or dependencies are required?
Requires Node.js and a locally installed and configured TaskWarrior (the `task` binary) – the server calls this binary for all operations.
Where does task data live?
Task data stays in your local TaskWarrior database; the server does not sync or store data externally.
What are the known limitations?
The server currently uses the unstable task `id` instead of the more reliable UUID; TaskWarrior may renumber IDs when tasks are added or removed.
Basic information
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