Convex Supermemory

Documentation from sholajegede/convex-supermemory, recorded October 23, 2026. APIs and setup may differ in the Bijection adaptation.

convex-supermemory

Give your Convex app long-term, semantically searchable memory with Supermemory. Reactive local memory and document state, direct REST integration.

Copy codeconst supermemory = new Supermemory(components.convexSupermemory, {
  apiKey: process.env.SUPERMEMORY_API_KEY!,
});

// Store a fact about a user
const { memoryId } = await supermemory.addMemory(ctx, {
  containerTag: userId,
  content: "Prefers dark mode and terse responses",
});

// Recall it later with semantic search
const { results } = await supermemory.search({
  containerTag: userId,
  query: "how does this user like responses formatted?",
});

What this does

An AI agent is only as good as what it remembers between calls. Supermemory is a memory API purpose-built for this: you write facts and documents into a containerTag (typically one per user or agent), and it handles embedding, chunking, and semantic search so you can recall the right context later — without you running your own vector database.

This component wraps Supermemory's REST API directly (no SDK dependency) and mirrors everything you write into Convex tables, so you get:

• Fast-path memory — addMemory() stores a single fact immediately, no processing pipeline
• Document ingestion — addDocument() sends larger content through Supermemory's extraction/chunking pipeline, with refreshDocument() to poll status
• Semantic search — search() proxies Supermemory's hybrid RAG + memory search live
• Reactive local state — every memory and document is queryable from Convex without an extra API call
• Forgetting — forgetMemory() / deleteDocument() keep local state in sync with what Supermemory actually removes

Table of Contents

• Install
• Quick Start
• Usage
• Memories vs. Documents
• API Reference
• Type Reference
• Database Schema
• Container Tags
• Testing
• Example App
• Limitations
• Troubleshooting
• Contributing
• Changelog

Install

Copy codenpm install convex-supermemory

Requirements: Convex v1.33.1 or later, Node.js 18+, a Supermemory API key

Quick Start

Three steps to add memory to your Convex app.

1. Add the component

In convex/convex.config.ts:

Copy codeimport { defineApp } from "convex/server";
import convexSupermemory from "convex-supermemory/convex.config";

const app = defineApp();
app.use(convexSupermemory);

export default app;

2. Set environment variables

Copy codenpx convex env set SUPERMEMORY_API_KEY sm_xxxxxxxxxxxx

3. Initialize the client

In convex/memory.ts:

Copy codeimport { components } from "./_generated/api";
import { Supermemory } from "convex-supermemory";

export const supermemory = new Supermemory(components.convexSupermemory, {
  apiKey: process.env.SUPERMEMORY_API_KEY!,
});

Import supermemory from this file in any Convex action that needs to read or write memory.

Usage

Remember a fact

Copy codeexport const remember = action({
  args: { userId: v.string(), fact: v.string() },
  handler: async (ctx, args) => {
    return await supermemory.addMemory(ctx, {
      containerTag: args.userId,
      content: args.fact,
      isStatic: true, // long-term fact, not a fading conversational detail
    });
  },
});
// Returns: { memoryId }

Recall with semantic search

Copy codeexport const recall = action({
  args: { userId: v.string(), query: v.string() },
  handler: async (ctx, args) => {
    return await supermemory.search({
      containerTag: args.userId,
      query: args.query,
      limit: 5,
    });
  },
});
// Returns: { results: [{ documentId, score, summary, chunks, ... }], total }

Forget a memory

containerTag is required here too — Supermemory scopes the delete by it, not just by memoryId.

Copy codeexport const forget = action({
  args: { userId: v.string(), memoryId: v.string() },
  handler: async (ctx, args) => {
    return await supermemory.forgetMemory(ctx, {
      containerTag: args.userId,
      memoryId: args.memoryId,
    });
  },
});
// Returns: { forgotten: boolean }

List a user's memories reactively

Copy codeexport const getMemories = query({
  args: { userId: v.string() },
  handler: async (ctx, args) => {
    return await supermemory.listMemories(ctx, { containerTag: args.userId });
  },
});

Memories vs. Documents

Supermemory exposes two ways to write content, and this component exposes both:

• addMemory() — for short, discrete facts ("the user is on the Pro plan", "prefers metric units"). No processing delay; usable in search immediately.
• addDocument() — for longer content (a support transcript, a page of documentation, a whole conversation) that needs to be chunked and embedded. Processing is asynchronous — call refreshDocument() to check on status (queued → extracting → chunking → embedding → indexing → done).

API Reference

Type Reference

Copy codetype AddMemoryArgs = {
  containerTag: string;
  content: string;
  isStatic?: boolean;
  metadata?: Record<string, unknown>;
  forgetAfter?: number;   // ms epoch
  forgetReason?: string;
};

type AddDocumentArgs = {
  containerTag: string;
  content: string;
  customId?: string;
  metadata?: Record<string, unknown>;
};

type SearchArgs = {
  containerTag: string;
  query: string;
  limit?: number;
  rerank?: boolean;
  includeFullDocs?: boolean;
};

type SearchResponse = {
  results: Array<{
    documentId: string;
    title: string | null;
    score: number;
    summary: string | null;
    content: string | null;
    chunks: Array<{ content: string; score: number; position: number; isRelevant: boolean }>;
  }>;
  total: number;
  timing?: number; // ms, when Supermemory reports it
};

Database Schema

Copy codememories: {
  memoryId, containerTag, content, isStatic, metadata?,
  forgetAfter?, forgetReason?, forgotten,
  createdAt, updatedAt,
}

documents: {
  documentId, containerTag, content?, customId?, metadata?, status,
  title?, summary?,
  createdAt, updatedAt,
}

getStats(), listRecentMemories(), and listRecentDocuments() read across these tables directly with a full scan — fine for a dashboard or history view, not intended as a high-volume production query path.

Container Tags

Supermemory scopes everything — writes, search, and profiles — by containerTag. Use one per user for personal memory, or one per agent/workspace for shared memory. Search only ever looks within the container tag you pass, so pick a convention early (this component doesn't enforce one).

Testing

Copy codenpm run test

Component logic is tested with convex-test in src/component/lib.test.ts. Import convex-supermemory/test in your own app to register this component's schema against your test instance.

Example App

example/ is a full Vite + React demo that exercises the entire component end to end against your own Supermemory account:

• Memories — add a fact with addMemory() (with suggestion chips to try), forget it with forgetMemory(), all reactive.
• Documents — ingest longer content with addDocument(), poll status with refreshDocument(), remove it with deleteDocument().
• Search — run search() against whichever containerTag is selected, showing result score, matching chunks, and Supermemory's own reported total/timing.
• containerTag switcher — a row of chips lets you flip between a few demo users live, so you can see the exact same actions land in completely separate memory spaces.
• History — every memory and document ever written in the deployment, newest first, across every containerTag. Expand a row for full detail, or hit Recreate live to replay it as a brand-new memory/document.
• Activity console — a side-docked live log of every call this app makes into the Supermemory client, including real API errors (e.g. Supermemory returns 409 if you try to delete a document that's still processing).

Run it from the repo root:

Copy codenpm install --legacy-peer-deps
npx convex env set SUPERMEMORY_API_KEY sm_xxxxxxxxxxxx
npm run dev

npm run dev starts the Convex backend and the Vite frontend together — there's no need to cd example or run either one separately.

Limitations

• search() always calls Supermemory live — results are not cached or mirrored into Convex tables, since they're a ranked view over the underlying memories/documents rather than durable records themselves.
• Document processing is asynchronous; this component does not poll for you. Call refreshDocument() on a schedule (e.g. a Convex cron or scheduled function) if you need status without a user-triggered refresh.
• forgetMemory() reflects whatever forgotten value Supermemory returns — if Supermemory forgets asynchronously, the local record may briefly still show forgotten: false.
• deleteDocument() throws if Supermemory reports the document is still processing (409) — retry after the document reaches a terminal status (done/failed).

Troubleshooting

401/403 from Supermemory — confirm SUPERMEMORY_API_KEY is set and starts with sm_.

Search returns nothing — confirm you're searching the same containerTag you wrote memories/documents into; container tags are exact-match scopes, not fuzzy. If the document was ingested moments ago, give it a few seconds to finish indexing even after refreshDocument() reports done.

Document stuck in queued/extracting — large documents can take longer to process; call refreshDocument() again after a short delay.

Deleting a document fails with a "still processing" error — Supermemory returns 409 for a document that hasn't reached a terminal status yet; wait for refreshDocument() to report done or failed, then delete.

Contributing

See CONTRIBUTING.md.

Changelog

See CHANGELOG.md.