TaskFlow MCP 🔄✅

What is TaskFlow MCP?

TaskFlow MCP is a task management Model Context Protocol (MCP) server that helps AI assistants break down user requests into manageable tasks and track their completion. It enforces a structured workflow with user approval steps to ensure tasks are properly tracked and users maintain control over the process.

How to use TaskFlow MCP?

Install it globally with npm install -g @pinkpixel/taskflow-mcp and start with taskflow-mcp, or run locally with npx @pinkpixel/taskflow-mcp. Configure the server by setting the TASK_MANAGER_FILE_PATH environment variable and add it to your MCP client’s mcp_config.json. AI assistants interact with TaskFlow MCP through tools like plan_task, get_next_task, and mark_task_done.

Key features of TaskFlow MCP?

• Break down complex requests into tasks and subtasks
• Enforce user approval steps for quality control
• Persist tasks to disk in JSON or YAML format
• Export task status reports in Markdown, JSON, or HTML
• Track project and task-level dependencies with version information
• Archive completed requests and restore full history when needed

Use cases of TaskFlow MCP?

• AI assistants managing multi-step project plans with user confirmation
• Breaking a website creation request into design, implementation, and testing tasks
• Tracking progress of complex requests with subtasks and dependencies
• Archiving finished work to keep active task lists clean while preserving history
• Exporting task status reports for sharing with team members

FAQ from TaskFlow MCP

What file formats does TaskFlow MCP support for persistence?

TaskFlow MCP supports both JSON and YAML formats, automatically detected by the file extension (.json, .yaml, .yml). YAML is recommended for better handling of multiline content and human readability.

How do I set the tasks file path?

Use the TASK_MANAGER_FILE_PATH environment variable. You can specify absolute paths (e.g., /home/user/tasks.yaml) or relative paths (e.g., ./project-tasks.yaml). A custom base directory can be set with TASK_MANAGER_BASE_DIR.

Does TaskFlow MCP require any runtime dependencies?

It runs on Node.js and is installed via npm. No additional runtime services or databases are required—all data is persisted to a local file.

How does the archive system work?

Archives can be manual (using the archive_completed_requests tool) or automatic (set ARCHIVE_MODE=auto-on-complete). Archived requests can be browsed, searched, and restored using dedicated tools like list_archived_requests and restore_archived_request.

What transport does TaskFlow MCP use?

TaskFlow MCP is a standard MCP server that communicates over stdio, as configured in the MCP client’s mcp_config.json via the command and args fields.