Demos
Prove memory recall in minutes. Show one story: a SaaS copilot remembers a user in session 1, then answers a different question in session 2 without asking again.
Fastest proof: Playground
Start here — open Playground first. No terminal, no API key.
Flow: Save memory → Search recall → Build context. Playground shows Context ready (prompt-ready text). It does not run an LLM reply — that is what your app or the SaaS copilot starter does.
Playground walkthrough (film this)
Same story everywhere: session 1 save → session 2 ask → visible recall.
| Step | What to show | Copy |
|---|---|---|
| 1 | Open Playground (no API key) | "Prove your AI product can remember users." |
| 2 | Turn 1 — Save | "User prefers weekly email digests and dark mode UI." |
| 3 | Turn 2 — Ask | "How should the dashboard feel for this user?" |
| 4 | Build context | Context ready panel fills with prompt-ready text |
| 5 | Optional | Copy context_text — that goes into your LLM prompt |
Do not search the exact same text you just saved on turn 1.
Do show the context panel and recalled preferences. Do not lead with architecture, embeddings, or MCP tool catalogs.
Flagship code demos
| Link | |
|---|---|
| SDK quickstart | examples/sdk-quickstart |
| Next.js starter | starters/saas-copilot-nextjs |
| Film script | SAAS_COPILOT_DEMO_SCRIPT.md |
export MEMORYNODE_API_KEY="mn_live_..."
node examples/sdk-quickstart/index.mjsMap ownerId to your app's logged-in user ID.
Before / after
| Before | After |
|---|---|
| Empty recall / context panel | Non-empty context with user preferences |
| Generic AI reply (in your app) | Reply shaped by recalled context |
More examples
- Integration recipes — REST, OpenAI, Anthropic, MCP for builders
- REST (Node) · REST (Python)
- Two-call integration