A simple, beginner-friendly Model Context Protocol (MCP) server written in Python. It lets any MCP-compatible AI client (like Claude Desktop) manage a to-do list on your computer through five tools: add, view, get by ID, complete, and delete.
A Model Context Protocol (MCP) server that provides tools for managing todo items, including creation, updating, completion, deletion, searching, and summarizing tasks.
MCP server that exposes a TODO list API to AI assistants, enabling natural language management of tasks with create, read, update, and delete operations.
Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.
A simple MCP server that turns a JSON file into a todo list, letting users add, list, complete, delete, and clear tasks through natural language in MCP-compatible clients.
MCP servers for querying and submitting Ubuntu data via ubq, covering bugs, packages, versions, and merge requests with multiple authentication providers.
Enables Cursor on your laptop to connect to an MCP server on EC2 via SSE/HTTPS to manage a task queue stored in Postgres, supporting task listing, status updates, and work prompt generation.
A collection of over 20 specialized MCP servers that enable LLMs to manage customers, jobs, scheduling, invoicing, materials, and more in Housecall Pro's field service management system.
Enables AI assistants to manage todo lists through natural language by creating, listing, updating, completing, and deleting tasks stored in Firebase Firestore. Supports custom system prompts for personalized task management workflows.
A Model Context Protocol server that enables AI assistants to interact with TickTick/Dida365 task management API, supporting operations like creating, reading, updating, and deleting tasks and projects.
A Model Context Protocol server that integrates with Atlassian's Jira and Confluence, enabling AI assistants to interact with these tools directly through features like issue management, page creation, and content search.
An MCP server that enables AI agents to manage a TODO list with user authentication via Stytch. It provides tools for creating, reading, updating, and deleting TODO items while handling identity and authorization.
An MCP server that enables AI assistants to interact with Atlassian Jira and Confluence across Cloud and Server/Data Center environments. It supports tasks like searching and summarizing documentation, managing Jira issues, and creating content through natural language.
Enables secure integration between GitHub and Jira with permission controls, allowing users to manage repositories, create issues and pull requests, and handle Jira project workflows through natural language. Supports OAuth authentication and comprehensive security enforcement for both platforms.