Uses SQLite database for persistent storage of tasks, enabling the MCP server to maintain task data beyond AI context limitations
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.
This server cannot be installed
local-only server
The server can only run on the client's local machine because it depends on local resources.
A Model Context Protocol server that provides persistent task management capabilities for AI assistants, allowing them to create, update, and track tasks beyond their usual context limitations.
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