About Tiny TODO MCP
Tiny TODO MCP is an MCP server that gives AI assistants persistent task tracking backed by SQLite. It supports task creation, updates, deletion, and search, including views of upcoming and overdue tasks.
Key features
- 01Create tasks with titles, descriptions, and due dates
- 02Mark tasks complete or incomplete
- 03Delete tasks
- 04Search by status and due dates
- 05View upcoming and overdue tasks
Use cases
- 01Track tasks beyond an AI session's context
- 02Maintain task completion status and deadlines
- 03Find upcoming or overdue items
MCP support
Tiny TODO MCP exposes task-management tools to MCP clients, enabling AI assistants to create, update, delete, and search persistent tasks. Its SQLite database stores task data.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMETiny 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.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.