Tiny TODO MCP
Tiny TODO MCP is a specialized server that implements the Model Context Protocol (MCP), allowing AI assistants to interact with persistent storage for tasks. This enables AI models to maintain context over time and create and manage tasks beyond their usual context limitations.
what is Tiny TODO MCP?
Tiny TODO MCP is a specialized server that implements the Model Context Protocol (MCP), allowing AI assistants to interact with persistent storage for tasks, enabling them to maintain context over time and manage tasks beyond their usual limitations.
how to use Tiny TODO MCP?
To use Tiny TODO MCP, integrate it with your AI assistant following the MCP protocol, allowing the assistant to create, update, delete, and search for tasks stored in a persistent SQLite database.
key features of Tiny TODO MCP?
- Create, update, and delete TODOs with titles, descriptions, and due dates.
- Search for tasks by completion status and due dates.
- View upcoming and overdue tasks for effective task management.
- Easy integration with AI assistants following the MCP standard.
use cases of Tiny TODO MCP?
- Extend AI capabilities with persistent task tracking.
- Enable AI assistants to manage tasks with due dates and completion status.
- Support for time-aware task reminders for upcoming and overdue tasks.
FAQ from Tiny TODO MCP?
- Can Tiny TODO MCP be integrated with any AI assistant?
Yes! Tiny TODO MCP is designed for easy integration with AI assistants that follow the Model Context Protocol.
- What kind of storage does Tiny TODO MCP use?
Tiny TODO MCP uses a SQLite database for persistent storage of tasks.
- How does Tiny TODO MCP handle errors?
Tiny TODO MCP provides consistent error handling and responses as per the MCP standard.
Tiny TODO MCP
A Model Context Protocol (MCP) server implementation providing persistent task management capabilities for AI assistants.
Overview
Tiny TODO MCP is a specialized server that implements the Model Context Protocol (MCP), allowing AI assistants to interact with persistent storage for tasks. This enables AI models to maintain context over time and create and manage tasks beyond their usual context limitations.
Features
TODO System
- Create TODOs: Store tasks with titles, descriptions, and due dates
- Update TODOs: Mark tasks as complete or incomplete
- Delete TODOs: Remove tasks from the system
- Search TODOs: Find tasks by various criteria including completion status and due dates
- Task Management: View upcoming and overdue tasks
Integration
- Follows the Model Context Protocol standard
- Designed for easy integration with AI assistants
- Provides consistent error handling and responses
Use Cases
- Extend AI capabilities with persistent task tracking
- Enable AI assistants to track tasks with due dates and completion status
- Support for time-aware task reminders (upcoming and overdue tasks)
Architecture
Tiny Memory MCP uses a SQLite database for persistent storage, with a clean layered architecture separating:
- Tool interface (MCP protocol implementation)
- Service layer (business logic)
- Repository layer (data access)
- Database layer (storage)
Each tool exposed through the MCP interface provides clear documentation of its capabilities, parameters, and return values.
