OpenAI SDK + Memanto

Add persistent memory to any OpenAI Node SDK agent with three ready-made tools, shipped as part of the @moorcheh-ai/memanto TypeScript SDK.

Prerequisites

Node.js 20+
uv (ships uvx) — the Memanto client spawns a local Memanto server via uvx on first use unless you pass baseUrl
Memanto / Moorcheh credentials — Moorcheh API key (cloud) or an on-prem backend (no Moorcheh API key). Set MOORCHEH_API_KEY or pass apiKey to new Memanto({ ... })
OpenAI API key — the quick start uses gpt-4o via runTools(), which reads OPENAI_API_KEY from the environment (or pass apiKey to new OpenAI({ ... })).
openai and zod installed in your app (optional peer dependencies of @moorcheh-ai/memanto)

Install

npm install @moorcheh-ai/memanto openai zod

openai and zod are optional peer dependencies of @moorcheh-ai/memanto — install them yourself in the host app. Importing @moorcheh-ai/memanto/openai without them installed will fail at module load with a standard Node resolution error.

Quick Start

import OpenAI from "openai";
import { Memanto } from "@moorcheh-ai/memanto";
import { createMemantoOpenAITools } from "@moorcheh-ai/memanto/openai";

const client = new OpenAI(); // reads OPENAI_API_KEY — powers runTools(), not Memanto tools
const memanto = new Memanto({
  agentId: "my-agent",
  apiKey: process.env.MOORCHEH_API_KEY, // omit when using on-prem; see On-Prem below
});

const runner = client.chat.completions.runTools({
  model: "gpt-4o",
  tools: createMemantoOpenAITools(memanto),
  messages: [
    { role: "user", content: "What milk does Alex like? Also note he switched to soy today." },
  ],
});

console.log(await runner.finalContent());

createMemantoOpenAITools returns an array of tools built with zodFunction, ready to hand to the OpenAI Node SDK’s runTools() helper — each tool auto-parses its JSON arguments against a Zod schema before invoking Memanto. Each tool’s description is written for the model to decide when to call it (e.g. recallMemory: “Call this before answering whenever the user refers to information from earlier or from a previous session”).

Available Tools

Tool	Backed by	Description
`recallMemory`	Recall	Semantic search over stored memories. `query` (required), `limit` (nullable — pass `null` for the default), `type` (nullable array of memory types to filter by, or `null` for no filter).
`rememberMemory`	Remember	Persist a durable fact/preference/decision/instruction. `content` (required), `type` (optional — server auto-classifies if omitted), `title`, `tags`.
`answerMemory`	Generate AI Answer	RAG-synthesized answer over stored memories. `question` (required), `limit` (nullable — pass `null` for the default).

answerMemory calls Memanto’s Generate AI Answer API (memanto.answer() → Moorcheh answer.generate). Memanto retrieves relevant memories and synthesizes a grounded response using Memanto’s configured LLM — not the model you pass to runTools(). Your agent model only decides when to call the tool and how to use the result. recallMemory and rememberMemory do not invoke an LLM.

Unlike the Vercel AI SDK and Mastra variants, this integration’s schemas use nullable fields (.nullable()) instead of optional ones, matching the OpenAI function-calling convention where the model must explicitly pass null rather than omit a field.

Options

createMemantoOpenAITools(memanto, {
  include: ["recallMemory", "answerMemory"], // expose a subset — omit for all three
  defaultLimit: 10,                           // default limit for recall/answer when the model doesn't specify one
});

Memory Types

type fields are constrained to Memanto’s 13 supported types via a shared MEMORY_TYPES export:

import { MEMORY_TYPES } from "@moorcheh-ai/memanto/openai";
// ["fact", "preference", "goal", "decision", "artifact", "learning", "event",
//  "instruction", "relationship", "context", "observation", "commitment", "error"]

See the Memory Types Reference for what each type means.

On-Prem

The integration talks to Memanto through the Memanto client, so it works identically against an on-prem backend — no code changes, just configure the backend once with the CLI. See On-Prem Overview and the TypeScript SDK Reference.

Next Steps

TypeScript SDK Reference for the full Memanto client API
Vercel AI SDK Integration for the equivalent AI SDK tools
Mastra Integration for the equivalent Mastra tools
Memory Types Reference

​OpenAI SDK + Memanto

​Prerequisites

​Install

​Quick Start

​Available Tools

​Options

​Memory Types

​On-Prem

​Next Steps

OpenAI SDK + Memanto

Prerequisites

Install

Quick Start

Available Tools

Options

Memory Types

On-Prem

Next Steps