"A task management app for scheduling appointments" matching MCP servers:

Provides a task passport system for handoff across AI harnesses, enabling users to list, open, create, and checkpoint tasks with stable IDs and verified state.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

An MCP server for Task Trellis that provides tools for AI coding agents to manage tasks, currently featuring a simple hello_world demonstration tool.

Enables AI agents to autonomously manage and improve execution processes for repetitive task types by storing reusable task contexts with associated artifacts (practices, rules, prompts, learnings) and providing full-text search across historical best practices.

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

Enables long-running coding or documentation tasks to save incremental checkpoints, resume after interruptions, restore any previous step, and hand off work across sessions or machines using only the Python standard library.

This MCP server enables agents to manage complex tasks by providing tools for registration, complexity assessment, breakdown into subtasks, and status tracking throughout the task lifecycle.

MCP 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.

Enables agents to select the provably optimal set of candidate actions under a budget, with optional conflicts and prerequisites, and to re-plan to the single best next action after each outcome. Also validates any proposed selection for feasibility.

A task management system for LLM-based agents that stores all tasks in a single tree, available immediately after the server starts.

Enables AI assistants to manage tasks through YAML-based storage with subtask suggestions, status updates, and Mermaid Gantt chart generation. Supports hierarchical task structures with attributes like dependencies, milestones, and parallel execution.

Open Task Relay provides free, bounded public-good tasks that autonomous AI agents can discover, complete, submit, and independently verify. Its public TypeScript source runs locally with a Cloudflare Workers-compatible runtime and SQLite/D1, exposing MCP over HTTP.

An MCP server that translates human GUI actions into machine-executable commands, enabling AI agents to control real software applications like Zoom, Excel, and WeChat via natural language or API calls.

Provides tools for coordinating AI agent work on one machine through a local SQLite-backed queue and kanban, including task creation, atomic claiming, lease renewal, completion/failure, listing, comments, and cancellation.

A campaign and task management MCP server for AI coding assistants, enabling dependency tracking, acceptance criteria, testing strategies, and progress monitoring for projects.

Enables intelligent task management with status tracking, dependency resolution, and automatic next task discovery based on preconditions and priorities. Supports hierarchical task structures with subtasks and flexible JSON-based configuration.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Provides specialized tools for portfolio health analysis, rebalance simulations, and trade execution via a single interface powered by MongoDB. It enables AI agents to manage investment portfolios while adhering to organizational governing rules, clearance guards, and rate limits.

A Model Context Protocol server providing comprehensive task management capabilities with support for project organization, task tracking, and automatic PRD parsing into actionable items.

Provides structured workflows (phases, gates, coordination) for AI agents, enabling complex task execution with quality enforcement and multi-agent coordination via Model Context Protocol.

Enables AI coding agents from different MCP-capable clients to exchange messages in real time through a shared in-memory broker. Supports agent registration, inboxes, and live event streaming without requiring a database.

An intelligent task management system that provides structured workflows for AI Agents to plan, decompose, and execute complex programming tasks. It features a dedicated research mode for technical investigations and a task memory function to optimize workflows and avoid redundant coding work.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

An autonomous task decomposition and execution agent that plans, executes, verifies, and commits code changes for engineering goals.

Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.

Exposes an agent orchestration task queue as an MCP tool interface, allowing agents to submit, list, get, and update tasks with typed validation.

Full autonomous project management MCP server enabling AI assistants to manage projects, sprints, tasks, bugs, proposals, and team collaboration via natural language.

An MCP server that integrates with AI editors like Cursor to maximize agentic capabilities while solving context window limitations, providing a Svelte UI for task planning and implementation tracking.

Enables AI agents to create, manage, and track tasks within plans using Valkey as the persistence layer. Supports plan and task management with Markdown notes, status tracking, and prioritization through multiple transport protocols (SSE, Streamable HTTP, STDIO).

Enables AI agents to decompose high-level goals into structured task plan DAGs with dependencies, acceptance criteria, and quality gates, and to validate or export those plans in multiple formats.