memento-ai (TypeScript)

Long-term semantic memory for AI agents. TypeScript implementation compatible with Python memento-ai.

Features

Zero-config MCP — just npx memento-ai-mcp with Claude Desktop/Cursor
SQLite local storage — no database setup required
Postgres support — scale up when you need it
Semantic search — find memories by meaning, not keywords
Durability tiers — core facts vs situational context vs episodic memories
Version chains — audit trail for memory updates
Cross-language — shares schema with Python memento-ai

Quick Start: MCP Server

Add memory to Claude Desktop, Cursor, or any MCP tool — zero config:

{
  "mcpServers": {
    "memento": {
      "command": "npx",
      "args": ["memento-ai-mcp"],
      "env": {
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}

That's it! Memories are stored locally in ~/.memento/memories.db.

MCP with Postgres (optional)

For cloud sync or multi-device, add DATABASE_URL:

{
  "mcpServers": {
    "memento": {
      "command": "npx",
      "args": ["memento-ai-mcp"],
      "env": {
        "DATABASE_URL": "postgresql://...",
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}

MCP Tools

Tool	Description
`remember`	Store a new memory
`recall`	Search memories by semantic similarity
`list_memories`	List all memories with optional filters
`forget`	Delete a memory by ID

Installation

npm install memento-ai
# or
pnpm add memento-ai

Programmatic Usage

SQLite (Zero Config)

import { SQLiteMemoryStore, openaiEmbeddings, Durability, MemoryType } from 'memento-ai';

const store = new SQLiteMemoryStore({
  embeddings: openaiEmbeddings({ apiKey: process.env.OPENAI_API_KEY }),
  // dbPath: '~/.memento/memories.db'  // optional, this is the default
});

await store.setup();

// Add a memory
await store.add(['user_123', 'preferences'], {
  text: 'User prefers dark mode',
  durability: Durability.CORE,
  memoryType: MemoryType.PREFERENCE,
});

// Search memories
const memories = await store.search(['user_123', 'preferences'], {
  query: 'UI settings',
  limit: 5,
});

// Don't forget to close
store.close();

Postgres (Neon Serverless)

import { neon } from '@neondatabase/serverless';
import { MemoryStore, openaiEmbeddings, Durability, MemoryType } from 'memento-ai';

const sql = neon(process.env.DATABASE_URL!);
const store = new MemoryStore({
  sql,
  embeddings: openaiEmbeddings({ apiKey: process.env.OPENAI_API_KEY }),
});

await store.setup();

// Same API as SQLite
await store.add(['user_123'], {
  text: 'User prefers dark mode',
  durability: Durability.CORE,
});

Embeddings Providers

// OpenAI (default)
import { openaiEmbeddings } from 'memento-ai';
const embeddings = openaiEmbeddings();

// Via Helicone (observability)
import { heliconeEmbeddings } from 'memento-ai';
const embeddings = heliconeEmbeddings({
  heliconeKey: process.env.HELICONE_API_KEY!,
});

// Custom provider
const embeddings: EmbeddingsProvider = {
  dimensions: 1536,
  async embed(texts) {
    // Your implementation
    return texts.map(() => new Array(1536).fill(0));
  },
};

Schema

Memories have the following structure:

interface Memory {
  id: string;
  text: string;
  durability: 'core' | 'situational' | 'episodic';
  memoryType?: 'fact' | 'rule' | 'decision' | 'preference' | 'context' | 'observation';
  confidence: number;
  source: 'explicit' | 'inferred' | 'system';
  validFrom: Date;
  validUntil?: Date;
  supersedes?: string;      // Previous version ID
  supersededBy?: string;    // Next version ID
  tags: string[];
  metadata: Record<string, unknown>;
}

Environment Variables

Variable	Description	Default
`OPENAI_API_KEY`	Required for embeddings	—
`DATABASE_URL`	Postgres connection (optional)	Uses SQLite
`ENGRAM_DB_PATH`	Custom SQLite path	`~/.memento/memories.db`
`ENGRAM_NAMESPACE`	Default namespace (comma-separated)	`default`

Cross-Language Compatibility

This package uses the same database schema as Python memento-ai. You can:

Write memories from Python, read from TypeScript
Share a database between Python and TypeScript services
Migrate between languages without data changes

License

MIT

memable

Package Exports

Readme