How does it prevent AI hallucinations in task management?

The skill enforces a 'No Hallucinated Actions' rule, meaning the agent only acts on data returned from actual MCP tool results and never assumes state without fetching fresh data from the database.

What is the Todo AI MCP Agent skill?

It is a specialized skill for Claude Code that provides patterns and logic for building AI agents capable of managing tasks via natural language using the Model Context Protocol (MCP).

What safety measures are included for deleting tasks?

The skill includes mandatory confirmation flows for all destructive actions like deleting or clearing tasks, ensuring the AI never deletes data without explicit user consent.

Can this skill handle multiple tasks at once?

Yes, it includes a multi-action handling pattern that parses multiple intents from a single user input and executes them sequentially with a composed response.

Todo AI MCP Agent

Name: Todo AI MCP Agent
Author: NaveedTechLab

byNaveedTechLab

Productivity & Workflow

Manages tasks and todos using natural language through Model Context Protocol (MCP) tool integrations.

About

The Todo AI MCP Agent skill provides a standardized framework for building reliable conversational agents specialized in task management. It emphasizes safety and reliability through core principles like preventing hallucinated actions, maintaining a stateless server architecture, and requiring explicit database-backed verification. This skill is ideal for developers looking to implement natural language intent mapping for CRUD operations, handle complex multi-action requests, and ensure that destructive actions are always confirmed by the user before execution.

Key Features

Hallucination-free database-backed memory
0 GitHub stars
Natural language intent-to-tool mapping
Automated reference resolution for ambiguous inputs
Sequential multi-action processing
Stateless agent design for session safety

Use Cases

Building conversational task management assistants
Implementing safe MCP-based tool workflows
Integrating AI-driven todo lists into existing apps

About

Key Features

Hallucination-free database-backed memory
0 GitHub stars
Natural language intent-to-tool mapping
Automated reference resolution for ambiguous inputs
Sequential multi-action processing
Stateless agent design for session safety

Use Cases

Building conversational task management assistants
Implementing safe MCP-based tool workflows
Integrating AI-driven todo lists into existing apps