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2025-03-23

Tiny Todo MCP est un serveur spécialisé qui implémente le protocole de contexte du modèle (MCP), permettant aux assistants d'IA d'interagir avec le stockage persistant pour les tâches. Cela permet aux modèles d'IA de maintenir le contexte au fil du temps et de créer et de gérer les tâches au-delà de leurs limitations de contexte habituelles.

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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.

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    Reviews

    3 (1)
    Avatar
    user_iVYN55b8
    2025-04-15

    DevOps MCP Servers by a37ai has exceeded my expectations! The seamless integration and high reliability have significantly improved our deployment process. The intuitive interface and detailed documentation make it incredibly user-friendly. Highly recommended for any DevOps team looking for robust server solutions. Check it out here: https://mcp.so/server/devops-mcp-servers/a37ai