Question 1

What is TaskFlow MCP?

Accepted Answer

TaskFlow MCP is a task management Model Context Protocol (MCP) server that helps AI assistants break down user requests into manageable tasks with subtasks, dependencies, and notes. It enforces a structured workflow with user approval steps.

Question 2

How does TaskFlow MCP integrate with AI assistants?

Accepted Answer

TaskFlow MCP exposes a set of tools that AI assistants can use to plan, execute, and track tasks. These tools include `plan_task`, `get_next_task`, `mark_task_done`, and others, allowing AI assistants to interact with the server to manage tasks efficiently.

Question 3

What is the Model Context Protocol (MCP)?

Accepted Answer

MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). An MCP server acts as a bridge, enabling AI models to access and interact with external data sources and tools.

Question 4

What are the key features of TaskFlow MCP?

Accepted Answer

Key features include task planning, subtasks, progress tracking, user approval, persistence, flexible management, detailed reporting, export options, dependencies tracking, and notes.

Question 5

How do I install TaskFlow MCP?

Accepted Answer

You can install TaskFlow MCP globally using `npm install -g @pinkpixel/taskflow-mcp` or locally using `npm install @pinkpixel/taskflow-mcp`.

Question 6

How do I start the TaskFlow MCP server?

Accepted Answer

If installed globally, use the command `taskflow-mcp`. If installed locally, use `npx taskflow-mcp`.

Question 7

How do I configure TaskFlow MCP?

Accepted Answer

By default, TaskFlow MCP saves tasks to `~/Documents/tasks.json`. You can change this by setting the `TASK_MANAGER_FILE_PATH` environment variable.

Question 8

How do I use TaskFlow MCP with AI assistants?

Accepted Answer

Create an `mcp_config.json` file with the necessary configuration details for your MCP client to connect to the TaskFlow MCP server.

Question 9

What workflow does TaskFlow MCP enforce?

Accepted Answer

TaskFlow MCP enforces a structured workflow including planning tasks, retrieving the next pending task, completing subtasks, marking tasks as done, waiting for approval, and repeating the process until all tasks are complete, followed by final approval of the entire request.

Question 10

What is UBOS and how does TaskFlow MCP fit in?

Accepted Answer

UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department. The TaskFlow MCP server on the UBOS Asset Marketplace provides a robust solution for structuring, tracking, and executing tasks within AI workflows, enhancing the capabilities of AI Agents.

Question 11

What tools are available in TaskFlow MCP?

Accepted Answer

Available tools include `plan_task`, `get_next_task`, `mark_task_done`, `approve_task_completion`, `approve_request_completion`, `open_task_details`, `list_requests`, `add_tasks_to_request`, `update_task`, `delete_task`, `add_subtasks`, `mark_subtask_done`, `update_subtask`, `delete_subtask`, `export_task_status`, `add_note`, `update_note`, and `delete_note`, `add_dependency`.

Question 12

How can I contribute to TaskFlow MCP?

Accepted Answer

Contributions are welcome! Please see the `CONTRIBUTING.md` file for guidelines.

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