Show HN: Rememori zero-dependency agent memory that runs anywhere JS runs

Rememori, a zero-dependency agent memory engine written in pure TypeScript, launched on Hacker News. The library provides memory primitives for AI agents via a three-verb API (remember, recall, forget) and runs anywhere JavaScript runs, including browsers, Node.js, and edge workers. It uses local embeddings and a bipartite knowledge graph to enable semantic recall without external servers.

Your agent forgets. Give it memory. rememori is an embedded memory engine in pure TypeScript. Zero dependencies, zero servers, zero native bindings. One file on disk — or IndexedDB in the browser. npm install rememori v0.3.0 · 0 dependencies · ~8 kB core · MIT rememori — Esperanto for “to remember”. A language built to run anywhere. Same idea. Every session ends the same way. The context window empties. The user's preferences, the decisions made, the names mentioned — gone. Fixing it usually means a vector database, an embedding pipeline and a retrieval service. All that, for a bot that needs to remember fifty things. Memory should be a primitive, not a platform. memori. rememori. forgesi. Remember, recall, forget — three verbs. That’s the API. remember stores text with its embedding, tags and extracted entities. recall ranks by cosine similarity × importance × time decay — plus a graph bonus for shared entities. forget deletes. Everything else is an option, not a method. Bring any embedder: Ollama for local privacy, any OpenAI-compatible endpoint, or your own function. The verbs are Esperanto, like the name. js import { Memory } from 'rememori'; import { ollama } from 'rememori/embedders'; const mem = await Memory.open './agent.mem', { embedder: ollama 'nomic-embed-text' , } ; await mem.remember 'User prefers dark mode', { tags: 'prefs' , importance: 0.8, } ; const hits = await mem.recall 'UI settings?', { limit: 5, halfLifeDays: 90, } ; await mem.forget hits 0 .id ; Don’t take our word for it. This section runs rememori in your browser. The embedding model downloads once ~30 MB, cached , then everything — embeddings, storage, semantic recall — happens on your machine. Open DevTools → Network and watch it stay silent. Downloads the MiniLM embedding model ~30 MB from Hugging Face, once. Your memories never leave this page. Ready. Give your agent a memory. Now. rememori ships as an MCP server https://github.com/GiorgioDotcom/rememori/tree/main/mcp . One command gives Claude Code — or Cursor, Windsurf, any MCP client — persistent memory across sessions. Embeddings run locally via Ollama; memories live in one file on your disk. claude mcp add rememori -- npx -y rememori-mcp Recall is more than similarity. Every memory links to the entities it mentions — a bipartite knowledge graph, built automatically at write time. At recall, memories sharing entities with the query get a bonus: cosine + graph × importance × decay So when the words don't match but the who does, the right memory still surfaces. Entity extraction is pluggable; the built-in heuristic costs zero dependencies and zero API calls. If it runs JavaScript, it remembers. Node ≥ 18 append-only file, one npm i Bun same file format, same API Browser IndexedDB via idb:// paths Edge workers bring a KV adapter — it's one interface Electron no rebuild, ever Native-binding memory engines compile per platform and stop at the browser's edge. Pure TypeScript ships everywhere the language does — this very page is the existence proof. What would you build? A support bot that remembers the customer Last ticket, preferred tone, the promise a colleague made two weeks ago. remember every message, recall before replying. Telegram, Discord, Slack — three lines each. A coding agent with cross-session memory Decisions, conventions, “we already tried that”. One .mem file next to the repo, versionable and greppable. A local-first app with semantic search Electron or Tauri note-taking, mail, research tools: recall by meaning without shipping your users' data to a server. Assistants under compliance Legal, health, finance. Memory that provably never leaves the device: IndexedDB storage plus local embeddings, auditable in the Network tab. A home-automation brain on a Raspberry Pi “Boiler serviced in March, technician was Rossi.” Nobody wants to run Postgres on a Pi. NPCs that hold a grudge Game characters that remember the player across saves — in-process, inside the game loop, zero infrastructure.