S I G N E T A I

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# S I G N E T   A I

**Bring your own context to any AI agent**

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**97.6% average LongMemEval answer accuracy**<br />
Readable record · inspectable recall · harnesses are replaceable

[Website](https://signetai.sh) · [Docs](https://signetai.sh/docs) · [Benchmarks](./docs/BENCHMARKING.md) · [Vision](VISION.md) · [Discussions](https://github.com/Signet-AI/signetai/discussions) · [Discord](https://discord.gg/Psdeg7sQm7) · [Contributing](docs/CONTRIBUTING.md) · [AI Policy](AI_POLICY.md)

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---

**Models change. Harnesses change. Providers change. Your context should not.**

Signet is the portable context layer for AI agents. It keeps identity,
memory, provenance, secrets, skills, and working knowledge outside any
single chat app, model provider, or harness. The execution surface can
change. The agent keeps its footing.

The job is simple: bring your own context to the agents you already use,
then keep that context inspectable and under your control. Signet runs
beneath Claude Code, OpenCode, OpenClaw, Codex, Hermes Agent, and other
harnesses so the durable layer survives the tool of the week.

Memory is ambient. Signet captures useful context between sessions,
preserves the raw record, indexes it for recall, and injects relevant
context before the next prompt starts. The agent wakes up with continuity
instead of asking you to rebuild the room by hand.

Why teams adopt it:
- less prompt re-explaining between sessions
- one context layer across agents, models, harnesses, and providers
- local-first storage with inspectable provenance and repair tools
- a path away from harness-locked behavioral context

## Quick start (about 5 minutes)

```bash
bun add -g signetai        # or: npm install -g signetai
signet setup               # interactive setup wizard
signet status              # confirm daemon + pipeline health
signet dashboard           # open memory + retrieval inspector
```

If you already use Claude Code, OpenCode, OpenClaw, Codex, or Hermes
Agent, keep your existing harness. Signet installs under it.

### Docker self-hosting

Run Signet as a containerized daemon with first-party Compose assets:

```bash
cd deploy/docker
cp .env.example .env
docker compose up -d --build
```

See [`docs/SELF-HOSTING.md`](docs/SELF-HOSTING.md) for token bootstrap,
backup, and upgrade runbook details.

## Bring your own context

Portable memory only matters if the agent can see the world you already
work inside. Signet is built around ordinary context, not a special
knowledge-base ritual: project notes, transcripts, markdown files, PDFs,
URLs, identity files, decisions, preferences, and the corrections that
shape how work actually happens.

The durable record stays readable. The semantic layer helps the agent
navigate it. Retrieval is a lens over the record, not a replacement for
it. When a summary is stale, conflict-heavy, or decision-critical, the
agent can climb back down to the source.

## First proof of value (2-session test)

Run this once:

```bash
signet remember "my primary stack is bun + typescript + sqlite"
```

Then in your next session, ask your agent:

```text
what stack am i using for this project?
```

You should see continuity without manually reconstructing context.
If not, inspect recall and provenance in the dashboard or run:

```bash
signet recall "primary stack"
```

Want the deeper 

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