"Replicating ChatGPT Memory Functionality for Task Management and Skill Tracking" matching MCP servers:

Enables Claude to create, edit, run, and manage reusable skills stored locally, including executing scripts with automatic dependency management and environment variables. Works across all MCP-compatible clients like Cursor, Claude Desktop, and claude.ai.

Enables long-horizon autonomous task checkpointing and resumption through cryptographic event-sourced state persistence, idempotency key deduplication, timeout heartbeats, human-in-the-loop pause/resume tokens, and fail-safe recovery.

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

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 autonomous planning by decomposing prompts into directed acyclic task graphs and resolving dependency topologies for multi-agent pipelines.

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.

Enables users to decompose prompts into dependency-aware task DAGs for autonomous multi-stage planning and orchestration.

Slipstream - Built by Vektor Memory - a persistent multi-layered memory architecture. 4-layer associative graph memory (MAGMA) with autonomous REM cycle, CLI, DXT-MCP Cloak Tools.

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.

A self-hostable semantic skill registry for AI agents, providing searchable, versioned, and verified skills over a single MCP endpoint with per-agent private vaults and trust tiers.

Enables AI agents to manage, search, plan, and execute reusable skills while automatically enforcing always-on coding and reasoning guidelines. It provides workflow orchestration, permission-controlled execution, dynamic skill registration, and feedback-based ranking.

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.

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

Enables persistent skill management over the Model Context Protocol, allowing agents to use, write, list, and migrate skills backed by directory, Git, or S3 stores.

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.