"Designing UI (User Interfaces)" matching MCP servers:

Gives AI assistants a persistent memory across conversations, allowing them to remember user preferences, notes, and facts between chats.

Multi-user, file-backed MCP memory server enabling isolated namespaces and persistent memory across sessions and AI clients.

Provides brain-inspired long-term memory for MCP clients, enabling persistent user understanding across sessions with Chinese-optimized hybrid retrieval and evolving user profiles.

Central user-state database MCP server with durable profile facts and live virtual sensors (stress, room intensity) with configurable smoothing, readable by any agent or smart-home service.

Give your AI persistent, structured memory and let humans see it too. It stores project knowledge as Markdown files in a hierarchical tree, accessible via MCP tools and a built-in Web UI.

Enables LLM agents to persist, search, update, forget, summarize, and manage user cognitive memories through MCP tools.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

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Provides persistent memory for AI assistants like Claude, enabling them to remember user identity, projects, and conversations across sessions and platforms via natural language commands.

A personal digital twin MCP server that manages professional context, including skills, experience, and project learnings. It allows AI assistants to retrieve and update user preferences and career interests across different development environments.

Enables AI agents and MCP clients to run research as an explicit scientific process: forming hypotheses, designing and executing sealed experiments, capturing observations and artifacts, linking claims to supporting evidence, and reviewing provenance. Exposes coordinated MCP services so users can inspect, reproduce, and audit every step from question to conclusion rather than trusting an opaque final answer.

An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

Serves as a machine perception and action hub, enabling heartbeat monitoring, screen/window/clipboard sensing, todo management, long-term memory, and web/file operations through both CLI and MCP interfaces.

Persistent, searchable per-project memory for Claude Code using DuckDB and vector search, with rule enforcement and a management UI.

Self-hosted issue tracker built for agent-driven development. One binary, SQLite storage, MCP-native, with a web UI, REST API, and CLI for the humans.

A productivity coaching assistant designed for ADHD support that provides intelligent task management, goal tracking, and personalized recommendations. It utilizes a persistent memory system to learn user patterns and preferences, helping to reduce decision paralysis through actionable suggestions.

Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.

Fireproof ledger database with multi-user sync

Python stdio MCP server that interfaces with the Logseq local HTTP API, enabling tools to manage pages, blocks, queries, and graph configurations in Logseq.