"Designing a memory system for persona-based agents to improve user experience" matching MCP servers:

A local markdown memory and cross-agent context engine for AI coding assistants. It provides an MCP server with tools to search, add, retrieve, and distill persistent memory across tools like Claude Code, Cursor, and Zed.

Enables real-time auditing of LLM long-term memory to detect contradictions, user-introduced falsehoods, staleness, and unsourced fabrications, while providing a safe memory store with tools like recall, review, and restore.

Builds a searchable memory bank from persona-specific PDF content and exposes it as an MCP tool for querying.

MCP server that silently monitors state changes in structured data sources (e.g., government open data) and provides a pull-based channel for AI agents to retrieve real mutations since their last cursor.

Provides current weather information for any location and generates AI-powered responses using Google Gemini through FastMCP.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Cross-project memory for Claude Code, enabling local semantic recall and secure, git-versioned markdown storage of reusable knowledge across repositories.

Enables persistent storage and retrieval of decisions, settings, and operational rules across chat sessions, maintaining context continuity and decision consistency for long-term development projects through structured memory management.

Enables persona-configurable financial research and answers questions about 24 US-listed companies across three sectors, grounded in a SQLite database via MCP tools.

Enables AI models to interactively prompt users for input or clarification directly through their code editor. It facilitates real-time communication between assistants and users during development tasks.

AI-powered persona analysis and Focus Group Interview (FGI) system that creates dynamic personas from survey responses, generates contextual follow-up questions, tracks data freshness scores, and provides business insights on preferences and trends.

Enables AI coding assistants to query private academic paper collections via standard MCP tools, with hybrid retrieval, reranking, and inline citations.

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.

Enables AI to switch between 26+ expert personas on-demand with smart context detection, persona chaining, and 80%+ token savings through 'Submarine Mode' that keeps personas inactive until triggered.

Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

An MCP server for external computer-use that launches, observes, and interacts with any X11 application via AT-SPI2 accessibility tree and xdotool input injection.

Dynamic AI persona management for Claude with file-based storage. Switch between different AI personas mid-conversation or start conversations with pre-configured personas.

Enables persistent memory and semantic search for development workflows with hierarchical compression. Store and retrieve development knowledge across IDE sessions using natural language queries, circumventing context window limitations.

A lightweight, local-first MCP memory server for LLM agents that enables storing, searching, and retrieving agent memories with zero external dependencies.