Installation

Requirements

Dependency	Version
OpenClaw	v2026.4+
Node.js	18+ (Node 24/26 fully supported)
Qdrant	Running on :6333
LLM access	ANTHROPIC_API_KEY (default), or any OpenAI-compatible provider — see LLM provider

Qdrant can be started via Docker:

docker run -p 6333:6333 qdrant/qdrant

---

Install the plugin

# From npm (recommended)
openclaw plugins install openclaw-amem

# From a local checkout of the amem monorepo
pnpm --filter openclaw-amem build
openclaw plugins install --link ./packages/openclaw-amem

Updating

openclaw plugins update openclaw-amem

The gateway does not load the new build automatically. Restart it:

openclaw gateway restart

Know these two things before you update.

An update rebuilds node_modules, which is where the model cache lives by default. As a result, an update re-downloads 2.27 GB unless you have set AMEM_MODEL_CACHE to a path outside the plugin directory. Set it once. After that, updates do not require a download:

AMEM_MODEL_CACHE=~/.openclaw/model-cache

Check whether you still need any workaround you added. AMEM_EMBED_DTYPE=fp32 was needed on 2.0.0 and 2.0.1, whose default did not load. From 2.1.0 the default is correct and that variable can go. A stale override is not harmless. It pins you to a choice the release has moved past.

---

Configure openclaw.json

Add openclaw-amem to your plugin config and hook it into the memory slot:

{
  "plugins": {
    "allow": ["openclaw-amem"],
    "entries": {
      "openclaw-amem": {
        "enabled": true,
        "hooks": {
          "allowConversationAccess": true
        },
        "config": {
          "agentId": "main",
          "topK": 5
        }
      }
    },
    "slots": {
      "memory": "openclaw-amem"
    }
  }
}

Memory slot conflict

If your openclaw.json already has a memory slot assigned to another plugin (for example memory-core), you must replace it with openclaw-amem:

// ❌ Will cause amem to be silently ignored
"slots": {
  "memory": "memory-core"
}

// ✅ Correct — amem replaces memory-core
"slots": {
  "memory": "openclaw-amem"
}

On OpenClaw 2026.8.1, the slot alone is not enough. A second memory-kind plugin still loads, even with no slot and no entry in plugins.entries. Both plugins then register a tool named memory_search, and only one of them keeps the name. The gateway finds bundled plugins before installed ones, so memory-core wins and amem's memory_search tool is dropped.

Amem still serves the memory slot, so memory itself keeps working. The tool an agent calls is the other plugin's.

The gateway does report the drop, at level ERROR, in the structured log at /tmp/openclaw/openclaw-<date>.log. It does not appear in the gateway log:

plugin tool name conflict (openclaw-amem): memory_search

The name in brackets is the plugin whose tool was dropped, not the one that kept it.

So disable the other plugin in plugins.entries:

"entries": {
  "memory-core": { "enabled": false },
  "openclaw-amem": {
    "enabled": true,
    "hooks": { "allowConversationAccess": true },
    "config": { "agentId": "main", "topK": 5 }
  }
}

memory-core also does work that has nothing to do with the memory slot, such as writing its dream diary. If you disable it, that work stops as well.

Required: hooks.allowConversationAccess: true must be set explicitly. Without it, OpenClaw's security policy blocks the agent_end hook and automatic memory write-back will not work. The plugin writes memories only when you call memory_add manually.

If allowConversationAccess is not set, the plugin logs a startup warning. It also appends a notice to every memory_search result saying write-back is disabled. The plugin decides this once, by reading the configuration, rather than by waiting to see whether the hook ever fires.

---

Restart OpenClaw

openclaw gateway restart

On first run, the plugin downloads the bge-m3 ONNX embedding model (2.27 GB) and caches it locally. Subsequent restarts are instant.

If you upgrade rather than install fresh, no download occurs. An existing store keeps the model that built it. Moving to bge-m3 is a deliberate migration. If 2.27 GB is more than you want, see choosing a smaller model. The obvious candidate does not load. The ones that do give up either the context window or English.

---

LLM provider

The engine calls an LLM for note construction, linking, and evolution. Choose the backend with AMEM_LLM_PROVIDER:

• anthropic (default) — the Anthropic Messages API. Set ANTHROPIC_API_KEY.
• openai — the OpenAI Chat Completions API, which every OpenAI-compatible endpoint speaks. Set AMEM_LLM_PROVIDER=openai, point AMEM_LLM_BASE_URL at the endpoint, and set AMEM_LLM_API_KEY (or the standard OPENAI_API_KEY). This covers OpenAI, DeepSeek, OpenRouter, Groq, Together, and local servers (Ollama, vLLM, LM Studio — no key needed).

# DeepSeek
AMEM_LLM_PROVIDER=openai AMEM_LLM_BASE_URL=https://api.deepseek.com/v1 \
AMEM_LLM_API_KEY=sk-... AMEM_LLM_MODEL=deepseek-chat

# Local Ollama (keyless)
AMEM_LLM_PROVIDER=openai AMEM_LLM_BASE_URL=http://localhost:11434/v1 \
AMEM_LLM_MODEL=qwen2.5

For the full environment variable reference and model recommendations, see Configuration →.