What problem does it solve?
This Skill provides a stateless MCP-based task operation layer that lets AI agents perform CRUD ops (add, list, update, complete, delete) with database-backed persistence, enabling scalable and auditable task workflows.
Core Features & Use Cases
- Add, list, update, complete, delete tasks for any user with deterministic results.
- Tag management: attach and manage tags on tasks to support advanced filters and organization.
- MCP tool integration: expose tools via OpenAI-compatible schemas to AI agents for seamless agent-driven automation.
- Use case: An AI agent can create a new task, fetch user tasks with filters, mark a task complete, and tag with "urgent" in a single workflow, with all changes persisted in PostgreSQL.
Quick Start
To start, deploy a PostgreSQL-backed environment, initialize the MCP server, and expose the tools (add_task, list_tasks, complete_task, delete_task, update_task, add_tag_to_task) to AI agents through the MCP interface.