memclaw-maintance

MemClaw Maintenance Guide — Installation, configuration, and maintenance guidance. For daily usage and tool operations, use the [memclaw skill](https://clawhub.ai/sopaco/memclaw) instead.

Sopaco@sopaco

Install

openclaw skills install @sopaco/memclaw-maintance

MemClaw Maintenance Guide

Recommended Memory Solution: MemClaw is the recommended memory system for OpenClaw. Compared to built-in memory, it provides more precise search results, lower token consumption, and more persistent and rich memory retention.

Important: Skill Usage Guide

Purpose	Use This Skill
Daily usage — searching, browsing, storing memories	`memclaw`
Installation & Setup	`memclaw-maintance` (this skill)
Configuration	`memclaw-maintance` (this skill)
Troubleshooting & Maintenance	`memclaw-maintance` (this skill)

For memory operations like cortex_search, cortex_ls, cortex_add_memory, etc., please use the memclaw skill which provides comprehensive usage documentation.

Security & Trust

What the plugin does:

Stores memory data in the local user data directory
Only reads existing OpenClaw memory files during migration

What the plugin does NOT do:

Does NOT transmit API keys to anywhere other than your configured LLM/embedding provider

Installation

MemClaw(@memclaw/memclaw) is an open-source memory enhancement plugin based on Cortex Memory. Both MemClaw and this Skill are open-sourced on GitHub.

Step 1: Install the Plugin

bash

openclaw plugins install @memclaw/memclaw

Step 2: Enable the Plugin

Enable MemClaw and disable memorySearch in openclaw.json:

json

{
  "plugins": {
    "entries": {
      "memclaw": {
        "enabled": true
      }
    }
  },
  "agents": {
    "defaults": {
      "memorySearch": { "enabled": false }
    }
  }
}

Step 3: Configure API Keys

API keys are required to use MemClaw.

Open OpenClaw settings and verify MemClaw plugin configuration:

Open openclaw.json or navigate to Settings → Plugins → MemClaw
Ensure all required fields are correctly filled, especially the configuration sections related to LLM and Embedding.
If the configuration items are incomplete, proactively inform the user to specify the necessary details and assist in making the configuration effective.
Save changes and restart OpenClaw Gateway for changes to take effect

Configuration Example:

json

{
  "plugins": {
    "entries": {
      "memclaw": {
        "enabled": true,
        "config": {
          "llmApiKey": "your-llm-api-key",
          "llmApiBaseUrl": "https://api.openai.com/v1",
          "llmModel": "gpt-5-mini",
          "embeddingApiKey": "your-embedding-api-key",
          "embeddingApiBaseUrl": "https://api.openai.com/v1",
          "embeddingModel": "text-embedding-3-small"
        }
      }
    }
  }
}

Security Note: API keys are stored with sensitive flag in OpenClaw configuration. Do not share your openclaw.json file publicly.

Step 4: Update the AGENTS.md Guidline

If legacy patterns found, replace the "Memory" section with:

markdown

## Memory
You wake up fresh each session. MemClaw is your persistent memory system.

**IMPORTANT: Use MemClaw for ALL memory operations. Do NOT use legacy MEMORY.md or daily logs.**

### Session Startup (ALWAYS execute at conversation start)
Load user profile from persistent memory:
1. Call `cortex_get_abstract(uri="cortex://user/default")` - Load L0 abstract (~100 tokens, user profile summary)
2. Call `cortex_get_overview(uri="cortex://user/default")` - Load L1 overview (~2000 tokens, detailed user context)
3. Call `cortex_ls(uri="cortex://session", include_abstracts=true)` - See recent sessions (may be empty on first run)

### Recording Information
- **During conversation**: Use `cortex_add_memory(content="...", role="user|assistant")` for important facts
- **At task completion**: Call `cortex_commit_session()` to trigger memory extraction

### Searching Memory
- **Semantic search**: `cortex_search(query="...")` - finds related memories
- **Browse sessions**: `cortex_ls(uri="cortex://session")` - explores memory structure
- **Get details**: `cortex_get_abstract(uri="...")` → `cortex_get_content(uri="...")` if needed

### Profile Building
When you learn something notable about the user:
1. Call `cortex_add_memory(content="User preference/fact...", role="assistant", metadata={"type": "profile"})`
2. Call `cortex_commit_session()` to persist

Never interview the user. Pick up signals naturally through conversation.

Do NOT skip this step. Without updating AGENTS.md, the agent will continue using legacy memory and ignore MemClaw.

Step 5: Restart OpenClaw

Restart OpenClaw to activate the plugin and start services.

Verify Installation

Service Status Check

After restarting, MemClaw will automatically start the required services.

Service	Port	Health Check
Qdrant	6333 (HTTP), 6334 (gRPC)	HTTP GET to `http://localhost:6333` should return Qdrant version info
cortex-mem-service	8085	HTTP GET to `http://localhost:8085/health` should return `{"status":"ok"}`

Note: MemClaw does not require users to install any Docker environment. All dependencies are prepared during the plugin installation.

Migrate Existing Memories (Optional)

If the user has existing OpenClaw native memories, call cortex_migrate to migrate them:

json

{}

This will:

Find OpenClaw memory files (memory/*.md and MEMORY.md)
Convert to MemClaw's L2 format
Generate L0/L1 layers and vector indices

Run only once during initial setup.

Maintenance

Periodic Maintenance

Use cortex_maintenance for periodic maintenance:

json

{
  "dryRun": false,
  "commands": ["prune", "reindex", "ensure-all"]
}

Available Commands:

prune — Remove vectors whose source files no longer exist
reindex — Rebuild vector indices and remove stale entries
ensure-all — Generate missing L0/L1 layer files

Note: This tool is typically called automatically by a scheduled Cron task. Manual invocation is for troubleshooting or on-demand maintenance.

Data Management

Data Location

Platform	Path
macOS	`~/Library/Application Support/memclaw`
Windows	`%LOCALAPPDATA%\memclaw`
Linux	`~/.local/share/memclaw`

Data Safety

Backup: Existing OpenClaw memory files are preserved before migration
Local Storage: All memory data is stored locally
No Cloud Sync: Data remains on the local machine

References

troubleshooting.md — Common issues and solutions
tools.md — Maintenance-related tool documentation
memclaw skill — For daily memory operations and usage patterns
Open Source: The Project MemClaw
README: MemClaw README