LongMemory

// Overview

LongMemory is a memory engine for LLM applications and autonomous agents. The pitch in its own README is that it is neither plain RAG nor a bare vector database: content is stored immutably with provenance and a temporal history, so the store can answer not just "what do I know" but "what was true when", and it can show the evidence it used to answer.

Everything runs local-first. The default store is SQLite on your own disk, and reopening the same database restores nodes, worlds, entities, edges, temporal history, grounding and lifecycle state. Recall is token-bounded and comes in several modes — strict, historical, associative, grounded and multilingual — so the caller decides how much context to spend and how literal the match must be.

One TypeScript engine is exposed through every surface a team is likely to want: an npm library, a global CLI, an HTTP service, an MCP server for agent hosts such as Claude Desktop, GitHub Copilot and Codex, a dashboard, and a VS Code extension. A zero-dependency Python SDK talks to the self-hosted service over HTTP. The project is Apache-2.0 licensed.

// What it does

• Durable local-first storage on SQLite, with immutable content, provenance and temporal truth rather than overwritten facts
• Five recall modes — strict, historical, associative, grounded and multilingual — with explainable evidence selection and token-bounded context
• One TypeScript engine across npm, a CLI, HTTP, MCP, a dashboard and a VS Code extension
• Governed project memory plus Skills, Chat Memory, LLM-Wiki and CodeGraph layers
• Zero-dependency Python SDK that calls the self-hosted service, keeping the engine in one place
• Optional answer_from_evidence adapter that validates cited excerpts and makes at most one model call, leaving ordinary recall untouched

// Getting started

The in-memory path needs no service and no external database, so you can ingest and recall inside a single Node process before deciding how to deploy.

npm install longmemory

import { createMemory } from 'longmemory';

const memory = await createMemory();
await memory.ingest({
    user_id: 'alice',
    text: 'I prefer TypeScript for backend services',
});

const result = await memory.recall({
    text: 'What language does Alice prefer?',
    mode: 'strict',
});

console.log(result);
await memory.close();

const memory = await createMemory({
    store: 'sqlite',
    db_path: './longmemory.db',
    tenant_id: 'acme',
    user_id: 'alice',
});

npm install --global longmemory
longmemory init
longmemory recall "current project priorities" --mode associative

pip install longmemory-sdk

Commands and code are distilled from the project's own documentation — always check the official repo for the latest.

// When to use it

• Give a chat assistant memory that survives sessions without pushing user data to a hosted memory service
• Answer questions that depend on when something was true, using historical recall over an immutable, provenance-tagged store
• Share one memory store across Claude Desktop, Copilot and Codex by pointing each at the same MCP server
• Keep a project's governed memory — decisions, skills, code graph — beside the repo instead of in a vendor account

// How LongMemory compares

LongMemory alongside other open-source agent memory tools AI/TLDR tracks, ranked by GitHub stars.