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88 lines
4.2 KiB
Text
88 lines
4.2 KiB
Text
---
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title: "Supermemory local"
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sidebarTitle: "Overview"
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description: "State-of-the-art memory, running on your machine. One binary, zero config."
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icon: "server"
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---
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Supermemory runs on your own hardware. It's the same memory engine behind the [hosted platform](https://console.supermemory.ai) — ingestion, memory extraction, hybrid semantic search, and the full API — as a single self-contained binary.
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<CodeGroup>
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```bash curl
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curl -fsSL https://supermemory.ai/install | bash
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```
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```bash npx
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npx supermemory local
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```
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</CodeGroup>
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No Docker. No database to provision. No config files. It boots in seconds with everything built in, and it's [open source](https://git.new/memory).
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## Zero config, actually
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Run the binary with nothing set and you get a complete memory system:
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- **The Supermemory graph engine, embedded** — created automatically on first boot. No database to stand up, no connection strings.
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- **Built-in local embeddings** — default `Xenova/bge-base-en-v1.5` (768d) on your machine, no API key. Same provider stack as cloud if you opt into OpenAI, Gemini, or Ollama — see [Embeddings](/self-hosting/embeddings).
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- **An API key, generated for you** — printed on first boot, ready to paste into any SDK.
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- **The full Memory API** — `/v3/documents`, `/v4/search`, `/v4/profile`, spaces, the works.
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The only thing you bring is a model. In production, Supermemory runs its own proprietary models, purpose-tuned for long-horizon data understanding and memory extraction. Self-hosted, the same pipeline runs on whatever model you point it at — OpenAI, Anthropic, Gemini, Groq, or any OpenAI-compatible endpoint. Bring a key and go. Or don't bring one at all:
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## Runs fully offline
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Supermemory works with any OpenAI-compatible endpoint, which means it runs end-to-end on your machine with a local model — Ollama, LM Studio, vLLM, llama.cpp. `gpt-oss-20b` is a great fit:
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```bash
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OPENAI_BASE_URL=http://localhost:11434/v1 \
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OPENAI_API_KEY=ollama \
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OPENAI_MODEL=gpt-oss:20b \
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supermemory-server
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```
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Local graph engine, local embeddings, local LLM. Your data never leaves the building.
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## Drop-in with your existing code
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The self-hosted server speaks the same API as the hosted platform. Point any Supermemory SDK at it with a one-line change:
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```typescript
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const client = new Supermemory({
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apiKey: "sm_...", // printed on first boot
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baseURL: "http://localhost:6767",
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})
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```
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Everything in the [Memory API docs](/quickstart) works the same way. The coding plugins do too — [Claude Code](/integrations/claude-code), [Codex](/integrations/codex), and [OpenCode](/integrations/opencode) all target your local server with `SUPERMEMORY_API_URL=http://localhost:6767`.
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## Self-hosted vs. the platform
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Self-hosted is free, open source, and great for local development, air-gapped environments, and privacy-sensitive workloads. The hosted platform is where the full product lives:
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| | Self-hosted | Platform |
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|---|---|---|
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| Full Memory API | ✅ | ✅ |
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| Hybrid semantic search | ✅ | ✅ |
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| Embeddings | Local default (or OpenAI / Gemini / Ollama) | Same provider stack, managed |
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| File ingestion (PDFs, images) | ✅ | ✅ |
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| [Connectors](/connectors/overview) (Google Drive, Notion, Gmail, OneDrive) | — | ✅ |
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| [Supermemory MCP](/supermemory-mcp/mcp) | — | ✅ |
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| Memory extraction | Your model, your key | Proprietary long-horizon models — higher quality, cheaper at scale |
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| Infrastructure | Your machine | Globally distributed, scales with you |
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If you outgrow a single machine — or want connectors, MCP, and the best-tuned extraction pipeline — [the platform](https://console.supermemory.ai) is one `baseURL` change away. Running this for a team or organization? See [Local vs. Enterprise](/self-hosting/local-vs-enterprise).
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## Next steps
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<CardGroup cols={3}>
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<Card title="Quickstart" icon="play" href="/self-hosting/quickstart">
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Install, run, and store your first memory in under two minutes
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</Card>
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<Card title="Configuration" icon="settings" href="/self-hosting/configuration">
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Every environment variable: LLM providers, storage, auth, tuning
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</Card>
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<Card title="Embeddings" icon="waypoints" href="/self-hosting/embeddings">
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Local default, remote providers, multilingual, dimension lock
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</Card>
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</CardGroup>
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