"Claude Desktop with persistent memory and artifact library system" matching MCP servers:

A self-hostable MCP server that provides permanent memory for AI agents using Postgres + pgvector for semantic search and Markdown file sync.

A persistent memory system for Claude using LanceDB, enabling semantic search, local embeddings, and tools to manage topics, memories, and todos across conversations.

Enables Claude to recall and query past conversations through a local knowledge graph and vector index, with tools for searching memory, retrieving related entities, and adding new memories.

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.

Provides a 'library keeper' sub-agent that ingests PDF/EPUB books and answers questions grounded in them via local embedding search, with deterministic classification and knowledge gap logging.

A persistent semantic memory system for Claude Code, using vector search and a judgment ledger to surface prior decisions and calibrate predictions.

A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

Enables AI assistants to remember user information and preferences across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage.

A local-first MCP server for persistent memory with vector search, metadata filtering, fact tracking, and graceful degradation when dependencies fail.

Provides persistent semantic memory for Claude Code and Claude Desktop with fully offline local embeddings and HNSW indexing, enabling memory storage, semantic search, listing, and deletion across sessions.

Provides token-efficient semantic search and document retrieval by indexing PDFs, text, and markdown files into local notebooks using ChromaDB. It enables AI agents to query relevant passages from large documents through local embedding models like Hugging Face or Ollama.

Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.

Provides persistent memory for MCP clients, enabling them to remember user preferences and behaviors across conversations using vector search and Cloudflare's infrastructure.

A production-ready MCP server for persistent AI memory across LLMs like Claude and ChatGPT. Provides automatic conversation backup, multi-user support, and multi-storage (PostgreSQL, Redis, Qdrant).

Enables AI assistants to remember user information across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage and retrieval.

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

A fully-local AI memory system that saves notes, code, and terminal output to a vector database via Ollama and LanceDB, enabling context retrieval from terminal, API calls, or inside Claude Code.

A self-hosted MCP memory and state system for long-running AI relationships, storing source text locally with explicit memory tools and a web manager for humans.

A persistent, conflict-aware memory MCP server for AI coding assistants (Cursor, Claude Code).