# Mem0

> Adds a persistent memory layer that stores and retrieves user preferences and context across conversations using semantic search.

- Skill: `dvcrn/mem0` (Agent Skill, multi-file: 9 files)
- Install (CLI): `npx skillmds@latest add dvcrn/mem0`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dvcrn/mem0/raw
- Safety review: CAUTION (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML, Coding & Dev Tools, Productivity, RAG & Embeddings
- Tags: Conversation Context, Mem0, Memory, Nodejs, Openai, Semantic Search
- Author: dvcrn (https://skillmd.com/u/dvcrn)
- Updated: 2026-08-22
- Page: https://skillmd.com/skills/dvcrn/mem0

---


# Mem0 Memory Integration

Mem0 adds an intelligent, adaptive memory layer to Clawdbot that automatically learns and recalls user preferences, patterns, and context across all interactions.

## Core Workflow

### 1. Search Before Responding
Before answering user questions, search mem0 for relevant context:

```bash
node scripts/mem0-search.js "user preferences" --limit=3
```

Use retrieved memories to:
- Personalize responses
- Remember preferences
- Recall past patterns
- Adapt communication style

### 2. Store After Interactions

**Explicit Storage** (when user says "remember this"):
```bash
node scripts/mem0-add.js "Abhay prefers concise updates"
```

**Conversation Storage** (for context learning):
```bash
# Pass messages as JSON
node scripts/mem0-add.js --messages='[{"role":"user","content":"I like brief updates"},{"role":"assistant","content":"Got it!"}]'
```

## Available Commands

### Search Memories
```bash
node scripts/mem0-search.js "query text" [--limit=3] [--user=abhay]
```

Searches semantically across stored memories. Returns relevant memories ranked by relevance.

### Add Memory
```bash
# Simple text
node scripts/mem0-add.js "memory text" [--user=abhay]

# Conversation messages (auto-extracts memories)
node scripts/mem0-add.js --messages='[{...}]' [--user=abhay]
```

Mem0's LLM automatically extracts, deduplicates, and merges related memories.

### List All Memories
```bash
node scripts/mem0-list.js [--user=abhay]
```

Shows all stored memories for the user with IDs and creation dates.

### Delete Memories
```bash
# Delete specific memory
node scripts/mem0-delete.js <memory_id>

# Delete all memories for user
node scripts/mem0-delete.js --all --user=abhay
```

## What to Store vs Not Store

### ✅ Store These:
- **Explicit requests**: "Remember that I..."
- **Preferences**: Communication style, format choices
- **Personal context**: Work info, interests, family (non-sensitive)
- **Usage patterns**: Frequent requests, timing preferences
- **Corrections**: When user corrects your mistakes
- **Adaptive facts**: Current projects, recent interests

### ❌ Don't Store:
- Secrets, passwords, API keys
- Temporary context (unless explicitly requested)
- System errors or debug info
- Information already in MEMORY.md (avoid duplication)

## Complementing Clawdbot Memory

**Clawdbot MEMORY.md** (Structured, Deliberate):
- Permanent facts: Name = Abhay, Location = Singapore
- Reference data: Email, blog URL, Twitter handle
- Structured knowledge: Project details, credentials

**Mem0** (Dynamic, Learned):
- Preferences: "Abhay prefers concise updates"
- Patterns: "Usually asks for bus info at 8:30am"
- Adaptive context: "Currently interested in AI news"
- Behavioral: "Likes direct answers, minimal fluff"

**Use both together**: Check MEMORY.md for facts, check mem0 for preferences/patterns.

## Performance Benefits

- **+26% accuracy** over OpenAI Memory (LOCOMO benchmark)
- **91% faster** than full-context retrieval
- **90% fewer tokens** than including all conversation history
- **Sub-50ms** semantic search retrieval

## Configuration

Located in `scripts/mem0-config.js`:

```javascript
{
  embedder: "openai/text-embedding-3-small",
  llm: "openai/gpt-4o-mini",
  vectorStore: "memory" (local),
  historyDb: "~/.mem0/history.db",
  userId: "abhay"
}
```

Uses Clawdbot's OpenAI API key from environment (`OPENAI_API_KEY`).

## Integration Patterns

For detailed workflow patterns, error handling, and best practices, see:
- `references/integration-patterns.md`

## Programmatic Use

All scripts support `JSON_OUTPUT` environment variable for programmatic access:

```bash
JSON_OUTPUT=1 node scripts/mem0-search.js "query"
```

Returns JSON after human-readable output (look for `---JSON---` marker).

## Resources

### scripts/
- `mem0-config.js` - Configuration and instance initialization
- `mem0-search.js` - Search memories semantically
- `mem0-add.js` - Add new memories
- `mem0-list.js` - List all memories
- `mem0-delete.js` - Delete memories

### references/
- `integration-patterns.md` - Detailed best practices and patterns