ClawMemory Skill

Sovereign agent memory engine — self-hosted, privacy-first. All data stays local (SQLite) with optional Turso cloud sync.

Repo: https://github.com/clawinfra/clawmemory
Server port:

localhost:7437

✅ VERIFIED WORKING PATTERNS (copy-paste ready)

Start the server

cd /tmp/clawmemory && ./clawmemory serve --config config.json
# OR with defaults (SQLite at ./clawmemory.db, port 7437, Ollama at localhost:11434)
./clawmemory serve

Guard rules:

• Ollama must be running for vector search — if not, BM25-only mode activates automatically (no crash)
• Server binds

  localhost:7437

  by default — not exposed externally
• First run auto-runs migrations (safe to restart)

Store a fact manually

curl -s -X POST http://localhost:7437/facts \
  -H "Content-Type: application/json" \
  -d '{"text": "User prefers Python over Go for scripting", "category": "preference", "importance": 0.8}'

Search memory

# Hybrid BM25 + vector (best quality)
curl -s "http://localhost:7437/search?q=python+preference&limit=5" | python3 -m json.tool

# BM25-only (fast, no Ollama needed)
curl -s "http://localhost:7437/search?q=python+preference&limit=5&mode=bm25" | python3 -m json.tool

Extract facts from a conversation turn (auto-capture)

curl -s -X POST http://localhost:7437/extract \
  -H "Content-Type: application/json" \
  -d '{
    "turns": [
      {"role": "user", "content": "I always deploy to Hetzner, never AWS."},
      {"role": "assistant", "content": "Got it, using Hetzner for deployments."}
    ]
  }' | python3 -m json.tool

Get user profile

curl -s http://localhost:7437/profile | python3 -m json.tool

Forget a fact

curl -s -X DELETE http://localhost:7437/facts/<fact-id>

OpenClaw Plugin (TypeScript) — Auto-wire

The plugin at

plugin/

cd /tmp/clawmemory/plugin && npm install && npm run build
# Copy plugin/dist/ to OpenClaw plugins dir and enable in config

Plugin config in

openclaw.config.json

{
  "plugins": [
    {
      "id": "clawmemory",
      "path": "./plugins/clawmemory/dist/index.js",
      "config": {
        "serverUrl": "http://localhost:7437",
        "maxContextFacts": 10,
        "minImportance": 0.3
      }
    }
  ]
}

What it does automatically:

• Pre-turn: searches memory for relevant facts → injects as

  [Memory context]

  block into system prompt
• Post-turn: sends conversation turn to

  /extract

  → stores new facts

Config Reference (config.json)

{
  "server": { "host": "localhost", "port": 7437 },
  "store": {
    "sqlitePath": "./clawmemory.db",
    "tursoUrl": "",
    "tursoToken": ""
  },
  "extractor": {
    "endpoint": "http://localhost:8080/v1",
    "model": "glm-4.7",
    "apiKey": "placeholder"
  },
  "embed": {
    "ollamaUrl": "http://localhost:11434",
    "model": "qwen2.5:7b"
  },
  "decay": {
    "halfLifeDays": 30,
    "minImportance": 0.1,
    "intervalMinutes": 60
  }
}

Key tunables:

• extractor.endpoint

  → point at any OpenAI-compatible endpoint (GLM-4.7, local Ollama, Anthropic proxy)

• embed.model

  →

  mxbai-embed-large

  gives better separability than

  qwen2.5:7b

  for security classification tasks

• decay.halfLifeDays

  → reduce to 7 for short-lived contexts (task sessions), increase to 90 for long-term persona facts

❌ KNOWN BROKEN / DO NOT USE

• Turso sync with empty token — set

  tursoUrl: ""

  to disable; non-empty URL with empty token causes silent write failures
• Ollama

  llama3.2-vision

  for embeddings — wrong dimensionality, breaks vector search index; use

  qwen2.5:7b

  or

  mxbai-embed-large

• Multi-statement SQL migrations —

  go-libsql

  can't handle them; each migration must be a single statement

Build from source

git clone https://github.com/clawinfra/clawmemory /tmp/clawmemory
cd /tmp/clawmemory
go build ./...  # produces ./clawmemory binary
go test ./... -timeout 120s  # all tests should pass

CI status:

main

877384b

API Reference (quick)

/facts

{text, category, importance}

/extract

{turns: [{role,content}]}

/search

/profile

/facts/:id

/forget

{query}

Categories:

person

preference

fact

skill

relationship

event

goal

Integration with OpenClaw workspace

ClawMemory replaces manual

memory/YYYY-MM-DD.md

When to use ClawMemory vs daily notes:

• Daily notes: decisions, decisions-with-context, URLs shared, task state → still use these
• ClawMemory:

  User prefers X

  ,

  User's email is Y

  ,

  Project Z uses Go

  → queryable atomic facts