"Exploring Memory Persistence in DeepSeek Technology" matching MCP servers:

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.

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.

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.

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

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 households to maintain a shared, persistent family memory for tracking item locations, warranty dates, chores, and who said what and when. It exposes this memory to AI assistants and tooling through MCP-compatible endpoints.

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.

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.

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

Enables comprehensive management of OpenProject work packages, projects, comments, and relations through natural language. Supports creating, updating, and organizing tasks with assignees, watchers, hierarchies, and inter-task relationships.

A comprehensive MCP server for CalDAV calendar management, supporting multi-account CRUD operations, recurring events, tasks, journals, and advanced search.

Goodday‑MCP is a lightweight Model Context Protocol (MCP) server designed to seamlessly integrate with the Goodday project management platform via its API v2. It enables querying of projects, tasks, and users—without altering any data—making it ideal for secure context-aware applications

Enables AI assistants to interact with Vikunja task management instances, providing full task, project, label, team, user, and webhook management operations through subcommand-based tools.

MCP server for AFKBot PTO management that allows users to file and manage time-off requests from any MCP-compatible client.

A Model Context Protocol (MCP) server for Hubstaff API integration, enabling seamless time tracking, project management, and team collaboration through AI assistants.

Lets agents read a GitHub repository's live issues through read-only tools for listing, filtering, fetching details with comments and cross-references, searching, and exploring labels and milestones, with transparent pagination and provenance notes.

A minimal MCP server that demonstrates the entire protocol using a simple in-memory todo list, including tools, resources, prompts, and elicitation.

Repository-native protocol and MCP server for coordinating work items, documentation, changelogs, and project memory between humans and AI agents, using Markdown files in a Git repository as the canonical data source.

Enables an AI assistant to analyse, and when permitted edit, Primavera P6 Professional schedules on a Windows PC, whether they live in a standalone SQLite database or plain XER files. It provides critical path and float analysis, DCMA health checks, progress comparisons, and in-memory what-if scenarios, with write operations off by default and protected by dry runs, backups, and an edit log.

Enables project task management through MCP tools to create, list, and update tasks, with SQLite persistence.

MCP server enabling AI agents to create, update, search, assign, and complete tasks on TaskLogger.io via the TaskLogger REST API, with secure local credential management and token persistence.

Enables coding agents to set up and manage the environment around a project — deployments to GitHub, Vercel and Railway, secrets, domains, technology choices and business systems — with help that adapts from guided walkthroughs to terse facts. It also researches companies and drafts offers using the user's own model and tokens, and reads project goals, decisions and a public technology catalog.

A todo list MCP server with Tools, Resources, and Prompts, demonstrating MCP features and compatible with DeepSeek and Claude Code.

A complete todo management system with authentication and billing that enables AI assistants to create, manage, and track todos with user accounts, free tier limits, and database persistence.

A server that implements a checklist management system with features like task creation, progress tracking, data persistence, and item comments.

Provides structured external memory for AI assistants, enabling persistent context, branch notes, tacit knowledge, and checklists to overcome AI memory loss and context confusion.