MCP + MemoClaw — giving your Model Context Protocol tools persistent memory

Your AI agent forgets everything between sessions. You know this. You've probably hacked around it with MEMORY.md files, context-stuffing, or just re-explaining things every time you open a new chat. MemoClaw fixes this with semantic memory-as-a-service. But here's what most people miss: you don't need to write a single line of integration code. The memoclaw-mcp server exposes store, recall, and list as native MCP tools — which means any MCP-compatible client can use MemoClaw out of the box. Claude Desktop, Cursor, Windsurf, OpenClaw — if it speaks MCP, it gets persistent memory in under five minutes. What You'll Build By the end of this tutorial, your MCP client will be able to: Store memories with importance scores and tags Recall memories using semantic search (not just keyword matching) List and manage stored memories across sessions Isolate context per project using namespaces No REST calls. No SDK imports. Just tool use. Prerequisites Node.js 18+ An Ethereum wallet (MetaMask, Rai