Getting started

Implementing with (or as) an AI agent? The agents implementation guide is the scenario-driven version of this page: pick a deployment shape (single agent, team server, multi-tenant engine, fleet), follow its steps, and verify with the checklist.

Install

Docker (recommended — nothing touches the host):

docker pull ghcr.io/sealcroft/undercroft:latest    # or: docker build -t undercroft .
alias undercroft='docker run --rm -v undercroft-data:/data ghcr.io/sealcroft/undercroft:latest'

Prebuilt binaries (Linux x86_64/arm64, macOS Intel/Apple Silicon, Windows) are attached to every release, with SHA-256 checksums. Or native: cargo build --release → target/release/undercroft.

First palace

undercroft init                                   # master key + sealed 'default' vault
undercroft remember "We chose GraphQL for the mobile API" --wing backend --room decisions
undercroft mine ~/notes --wing personal           # documents
undercroft mine ~/.claude/projects --mode convos  # Claude Code sessions
undercroft search "why graphql"
undercroft wake-up                                # session-start context
undercroft verify                                 # HMAC + audit chain check

Palace location: $UNDERCROFT_HOME (default ~/.undercroft). Passphrase mode: export UNDERCROFT_PASSPHRASE before init and every command.

Wire into Claude Code

claude mcp add undercroft -- undercroft serve-mcp
undercroft hooks claude-code   # auto-save hook settings to paste

Continue with integrations, architecture, security model, and remote team server.