@biginformatics/openclaw-wagl

OpenClaw plugin that brings wagl DB-first memory to any agent.

• Auto-recall — injects relevant memories before each agent turn (before_agent_start hook)
• Auto-capture — saves the last assistant response after each turn (agent_end hook)
• Tools — wagl_recall and wagl_store available to the agent at runtime
• Memory slot — registers as memory-wagl, taking the OpenClaw memory slot

Install

openclaw plugins install @biginformatics/openclaw-wagl

Then add to openclaw.json:

{
  "plugins": {
    "slots": { "memory": "memory-wagl" },
    "entries": {
      "memory-wagl": {
        "package": "@biginformatics/openclaw-wagl"
      }
    }
  }
}

Requirements

1. wagl binary

Install wagl on the agent's host and ensure it is on PATH:

# Download the latest release binary for your platform
# https://github.com/BigInformatics/wagl/releases
cp wagl /usr/local/bin/wagl
chmod +x /usr/local/bin/wagl
wagl init   # creates ~/.wagl/memory.db

Set WAGL_DB to a stable path (recommended):

export WAGL_DB="$HOME/.wagl/memory.db"

Without WAGL_DB, wagl defaults to a path relative to $PWD which will vary.

2. Semantic recall (optional but recommended)

Semantic search requires:

• An OpenAI-compatible embeddings endpoint (e.g. Ollama on armada)
• The sqlite-vec extension (vec0.so)

# Point to your embeddings server
export WAGL_EMBEDDINGS_BASE_URL="http://your-ollama-host:11434"
export WAGL_EMBEDDINGS_MODEL="qwen3-embedding:0.6b"

# sqlite-vec: place vec0.so at a stable path and set SQLITE_VEC_PATH
# Download a pre-built vec0.so from the wagl releases page, or build from source:
#   cd wagl-cli && git submodule update --init && ./scripts/build-sqlite-vec-linux-x86_64.sh
#   cp third_party/sqlite-vec/linux-x86_64/vec0.so /usr/local/lib/
export SQLITE_VEC_PATH="/usr/local/lib/vec0.so"

Without semantic recall, the plugin still works — wagl_store persists memories and wagl_recall runs text-only matching (lower precision). The plugin degrades gracefully; it will not crash if SQLITE_VEC_PATH or embeddings are missing.

3. Systemd service (recommended for production)

If OpenClaw runs as a systemd user service, add a drop-in to persist env vars:

mkdir -p ~/.config/systemd/user/openclaw-gateway.service.d

cat > ~/.config/systemd/user/openclaw-gateway.service.d/wagl.conf << 'UNIT'
[Service]
Environment=WAGL_DB=/home/YOUR_USER/.wagl/memory.db
Environment=SQLITE_VEC_PATH=/usr/local/lib/vec0.so
Environment=WAGL_EMBEDDINGS_BASE_URL=http://your-ollama-host:11434
Environment=WAGL_EMBEDDINGS_MODEL=qwen3-embedding:0.6b
UNIT

systemctl --user daemon-reload
systemctl --user restart openclaw-gateway.service

Configuration

All config is optional — defaults work for a basic setup.

{
  "plugins": {
    "entries": {
      "memory-wagl": {
        "package": "@biginformatics/openclaw-wagl",
        "config": {
          "dbPath": "/home/user/.wagl/memory.db",
          "autoRecall": true,
          "autoCapture": true,
          "recallQuery": "who am I, current focus, working rules"
        }
      }
    }
  }
}

Key	Default	Description
dbPath	$WAGL_DB → $WAGL_DB_PATH → ~/.wagl/memory.db	Path to wagl DB
autoRecall	true	Inject recall context before each agent turn
autoCapture	true	Save last assistant message after each turn
recallQuery	"who am I, current focus, working rules"	Query used for auto-recall

Known limitations

• vec0.so is not yet bundled with the wagl binary — see wagl#17 for the tracking issue
• Without semantic embeddings, recall uses text-only matching which has lower precision

License

Apache 2.0 — Copyright 2026 Informatics FYI, Inc.