How do I install the Agent Memory skill?

Run npx skillmds@latest add modbender/agent-memory 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?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

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?

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

Agent Memory by modbender — Agent Skill

Name: Agent Memory
Rating: 4.666666666666667 (3 reviews)
Author: modbender

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.

modbender Updated Sep 9, 2026 12 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-memorydescription: 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 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) ```bash # 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 ```bash # 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](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)

Frequently asked questions