#todo

MCP server for Microsoft To Do via Microsoft Graph. MSAL device code flow, no client secret needed.

AI-powered social media ghostwriter with 21+ tools for content creation, scheduling, and multi-platform publishing. What it does: - Generate AI content tailored to your brand voice - Schedule posts across Twitter/X, LinkedIn, Instagram, and more - Manage drafts, media library, and queue slots - Track ghost writer personas and feedback Tools include: - presence_get, presence_list — manage your social presences - draft_create, draft_update, draft_generate_ai — create and enhance content - queue_add_slot, queue_update_slot — schedule publishing times - media_upload, media_library_list — manage images and videos - ghost_writer_list, feedback_submit — AI personas and improvement feedback Transport: Streamable HTTP (MCP spec 2025-03-26) Auth: Bearer token via Authorization header Endpoint: https://feedmansion.com/mcp Docs: https://feedmansion.com/en/help/mcp-setup/ or https://github.com/makerprism/feedmansion-ai-agents

Developer logbook as an MCP server. Notes, TODOs, reminders, and code TODOs — all queryable with natural language. SQLite-powered, zero config, zero AI costs. Auto-detects your project, supports recurring reminders, full-text search (FTS5), and batch operations.

MCP server that connects AI agents (Claude Code, Cursor, Codex) to Dida365/TickTick. 40 tools for tasks, projects, tags, habits, folders, and search — manage everything through natural language.

Manage your tasks with AI assistants. List, create, update, complete and delete tasks, view groups and statistics through Glintlint REST API.

MCP server allows agents to break tasks down and execute them sequentially.

A comprehensive and efficient Model Context Protocol (MCP) server for task management that works seamlessly with Claude, Cursor, and other MCP clients. Designed to minimize tool confusion and maximize LLM budget efficiency while providing powerful search, filtering, and organization capabilities across multiple file formats. ✨ Features - ⚡ Ultra-efficient design: Minimal tool count (5 tools) to reduce AI confusion - 🎯 Budget-optimized: Batch operations, smart defaults and auto-operations minimize LLM API calls - 🚀 Multi-format support: Markdown (`.md`), JSON (`.json`), and YAML (`.yml`) task files - 🔍 Powerful search: Case-insensitive text/status filtering with OR logic, and ID-based lookup - 📊 Smart organization: Status-based filtering with customizable workflow states - 🎯 Position-based indexing: Easy task ordering with 0-based insertion - 📁 Multi-source support: Manage multiple task files simultaneously - 🔄 Real-time updates: Changes persist automatically to your chosen format - 🤖 Auto WIP management: Automatically manages work-in-progress task limits - 🚫 Duplicate prevention: Automatically prevents duplicate tasks - 🛡️ Type-safe: Full TypeScript support with Zod validation - 🔒 Ultra-safe: AI has no way to rewrite or delete your tasks (unless you enable it), only add and move them

MCP Todo.txt Integration is an MCP server for managing Todo.txt tasks. Add, update, filter, and organize tasks programmatically via the MCP protocol. Features include searching, sorting, metadata, batch operations, and dynamic updates.

Simple mcp server for handling todo lists, for sake of practice and education

🔗 Model Context Protocol server for todo.txt files - Connect your todo.txt to AI assistants like Claude Desktop

A simple and effective MCP server to manage your todos

MCP Server for TODO Management System

This MCP server enables advanced task and project management via Claude Desktop and other MCP-compatible clients.

This repository provides an MCP (Model Context Protocol) server for interacting with the Todo App through Claude and other MCP-compatible AI tools. This project allows AI agents to access and manage todos using the standardized MCP interface.

barebones Todoist MCP server - deployed in Cloudflare

A demo project connecting AI assistants to a Todo app using Model Context Protocol. Features React frontend, FastAPI backend, and Claude Desktop integration.

A simple todo model context protocol (mcp) server

AI assistants and Google Tasks integration through Model Context Protocol.

Mirror of

API de gerenciamento de tarefas via WebSocket com execução modular de comandos e suporte a ferramentas, desenvolvida em TypeScript com banco SQLite. Projetada para integração com agentes de inteligência artificial.

Todo app using mcp server

Connect your LLM to interact with Todoist tasks and projects. Access all the Todoist API right from your LLM.

This app was built completely with cursor using the Box MCP server to find a PRD and coding guidelines.

A lightweight Model Context Protocol (MCP) server that enables natural language interaction with your Todoist tasks directly from your IDE. Built with simplicity and maintainability in mind.

Todoist MCP server for Claude, using python Astral UV

An MCP Server implementation with Todoist

Mirror of

Mirror of

Interact with Todoist to manage your tasks.