"Context Memory Systems and Technologies" matching MCP servers:

Provides AI clients with per-project todo management and persistent context notes via MCP, enabling task tracking and resume summaries.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Project Memory stores decisions, evidence, outcomes and reviewed lessons in local SQLite. Assistants retrieve bounded context through three MCP tools. People follow and plan work in a live workspace with an overview, sprint board, decision history, readable documents, skills and project maps. Offline exports remain available.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables AI clients to locally store and share tasks, work activities, long-term memory, knowledge, and people information, while allowing users to review saved content and generate briefings or reports through a web UI.

Fetches structured Jira issue context from a URL, enabling coding agents to quickly understand issue intent and implementation details.

A local, provider-neutral MCP server for repository-scoped issue handling. It provides a guarded interface to Linear, GitHub Issues, GitHub Projects v2, and Jira Cloud, with preview/apply safety and host-local configuration.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

An MCP server that gives LLMs read-only access to Microsoft Project Online (Project for the Web) via the Microsoft Graph API.

Provides memory and project tracking for Claude Code via MCP, enabling semantic search over past transcripts, durable notes, and structured project management with milestones, epics, tickets, and todos.

Provides AI-driven project memory management through structured prompts that help Claude parse tasks from specs, review code changes, sync with commit history, and maintain project documentation without directly accessing files.

Read-only MCP server that fetches a single Jira issue by key and returns its title, description, comments, attachment summary, and image attachments.

Persistent, branch-aware workflow state memory MCP server for AI coding assistants. Tracks tasks, accepted decisions, and active blockers to prevent session context bloat and speed up development.

A Model Context Protocol server that provides structured workflow tools for managing software development projects through different complexity levels, offering specialized modes for project planning, design, implementation, and documentation.

An MCP server that helps teams create, manage, and access structured project documentation through six core document types, leveraging AI to generate comprehensive project knowledge management.

Enables AI agents to store, search, and manage persistent memories, todos, kanban boards, reminders, and progress trackers in a local SQLite database.

A project state control plane for multiple AI agent sessions to share structured conclusions such as tasks, checkpoints, code maps, decisions, and handoffs. It enables agents to read and write persistent project state via MCP tools while humans track progress through a lightweight panel.

Enables AI clients to access a shared, authenticated memory and project management system with durable storage, task tracking, roadmaps, and semantic search, deployed on Cloudflare.

Bridges disconnected AI sessions with persistent project memory and automatic session handoff, integrating GitHub workflows for context-aware development.

An MCP server for intelligent memory and task management with semantic search, automatic task extraction, and knowledge graphs, enabling AI assistants to maintain context and learn project conventions.