How do I install the Agent Memory skill?

Run npx skillmds@latest add knownasnaffy/agent-memory-4 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Agent Memory safe to use?

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Which AI agents work with Agent Memory?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Agent Memory free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Agent Memory?

knownasnaffy (@knownasnaffy) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Agent Memory by knownasnaffy — Agent Skill

Name: Agent Memory
Author: knownasnaffy

Agent Memory

Full AI agent memory stack — Mem0 unified memory engine with vector search (Qdrant) and knowledge graph (Neo4j), plus SQLite for structured data. Complete setup script and tools. Give your OpenClaw agent a real brain with semantic recall, entity relationships, and structured storage.

knownasnaffy Updated Sep 21, 2026 0 repo stars

File contents

Agent Memory 🧠

Full intelligence layer: vector memory + knowledge graph + structured database.

When to Use

Storing and recalling facts semantically ("remember that Abidi prefers...")
Managing structured data: projects, contacts, tasks, bookmarks
Setting up the brain stack after container rebuild
Batch seeding memory with key facts

Usage

Memory Engine (Mem0 — vectors + graph)

# Store a fact
python3 {baseDir}/scripts/memory_engine.py add "Abidi's business focuses on Voice AI"

# Semantic recall
python3 {baseDir}/scripts/memory_engine.py search "what does Abidi's business do"

# List all memories
python3 {baseDir}/scripts/memory_engine.py get-all

# Test connections (Qdrant, Neo4j, Langfuse)
python3 {baseDir}/scripts/memory_engine.py test

Structured Database (SQLite)

# List tables
python3 {baseDir}/scripts/structured_db.py tables

# Insert data
python3 {baseDir}/scripts/structured_db.py insert projects '{"name":"MyProject","status":"active"}'

# Query
python3 {baseDir}/scripts/structured_db.py query "SELECT * FROM projects"

Setup & Seeding

# Install Python deps after container rebuild
bash {baseDir}/scripts/setup_brain.sh

# Batch seed with key facts
python3 {baseDir}/scripts/seed_mem0.py

Architecture

Mem0 — Unified AI memory (auto fact extraction, dedup, multi-level recall)
Qdrant — Vector database for semantic search
Neo4j — Knowledge graph for entities & relationships
SQLite — Structured data (projects, contacts, tasks, bookmarks)
Langfuse — Observability tracing on all operations

Credits

Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.

📅 Need help setting up OpenClaw for your business? Book a free consultation

---name: agent-memory-4description: Full AI agent memory stack — Mem0 unified memory engine with vector search (Qdrant) and knowledge graph (Neo4j), plus SQLite for structured data. Complete setup script and tools. Give your OpenClaw agent a real brain with semantic recall, entity relationships, and structured storage.license: MIT---# Agent Memory 🧠Full intelligence layer: vector memory + knowledge graph + structured database.## When to Use- Storing and recalling facts semantically ("remember that Abidi prefers...")- Managing structured data: projects, contacts, tasks, bookmarks- Setting up the brain stack after container rebuild- Batch seeding memory with key facts## Usage### Memory Engine (Mem0 — vectors + graph)```bash# Store a factpython3 {baseDir}/scripts/memory_engine.py add "Abidi's business focuses on Voice AI"# Semantic recallpython3 {baseDir}/scripts/memory_engine.py search "what does Abidi's business do"# List all memoriespython3 {baseDir}/scripts/memory_engine.py get-all# Test connections (Qdrant, Neo4j, Langfuse)python3 {baseDir}/scripts/memory_engine.py test```### Structured Database (SQLite)```bash# List tablespython3 {baseDir}/scripts/structured_db.py tables# Insert datapython3 {baseDir}/scripts/structured_db.py insert projects '{"name":"MyProject","status":"active"}'# Querypython3 {baseDir}/scripts/structured_db.py query "SELECT * FROM projects"```### Setup & Seeding```bash# Install Python deps after container rebuildbash {baseDir}/scripts/setup_brain.sh# Batch seed with key factspython3 {baseDir}/scripts/seed_mem0.py```## Architecture- **Mem0** — Unified AI memory (auto fact extraction, dedup, multi-level recall)- **Qdrant** — Vector database for semantic search- **Neo4j** — Knowledge graph for entities & relationships- **SQLite** — Structured data (projects, contacts, tasks, bookmarks)- **Langfuse** — Observability tracing on all operations## CreditsBuilt by [M. Abidi](https://www.linkedin.com/in/mohammad-ali-abidi) | [agxntsix.ai](https://www.agxntsix.ai)[YouTube](https://youtube.com/@aiwithabidi) | [GitHub](https://github.com/aiwithabidi)Part of the **AgxntSix Skill Suite** for OpenClaw agents.📅 **Need help setting up OpenClaw for your business?** [Book a free consultation](https://cal.com/agxntsix/abidi-openclaw)

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