mem9 is a persistent memory service for AI agents that preserves information across sessions and machines and can share it among multiple agents. It is used with OpenClaw, coding agents, workflow platforms, and custom clients that need shared storage and recall. The catalogue add-ons connect agents and workflows to mem9 memory.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/mem9-ai/mem9Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/plugins/mem9-ai/mem9/claude-plugin)<a href="https://agentmods.dev/plugins/mem9-ai/mem9/claude-plugin"><img src="https://agentmods.dev/badge/plugins/mem9-ai/mem9/claude-plugin/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/plugins/mem9-ai/mem9/claude-plugin"><img src="https://agentmods.dev/badge/plugins/mem9-ai/mem9/claude-plugin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
mem9 scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
{
"name": "mem9",
"version": "0.3.4",
"description": "Persistent cloud memory for Claude Code. Requires Node.js 18+, auto-initializes auth on startup, recalls memories on each user turn, and uploads structured conversation turns to mem9.",
"author": {
"name": "mem9-ai"
},
"homepage": "https://mem9.ai",
"repository": "https://github.com/mem9-ai/mem9",
"license": "Apache-2.0"
}
What it installs
The manifest is a name and a version. 3 skills, 5 hooks travel with it, and installing the plugin installs all of them — 51 tokens a session between them. Each is measured on its own page, and each can be installed alone.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 12 lines scan A 3982f2b9309f
mem9 is a plugin published in the GitHub repository mem9-ai/mem9 (1,225 stars, last pushed 9d ago), licensed Apache-2.0. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other plugins, from other repositories
openviking-memory
Long-term semantic memory for Claude Code, powered by OpenViking. Auto-recall relevant memories at session start and capture important information during conversations.
lingshu-memory
A plugin that connects a coding agent to a long-term memory service and supplies 16 work rules. It supports memory across conversations and records whether saved information was committed.
causal-memory
Persistent causal memory for Claude Code — decisions, outcomes, and lessons that survive compaction. Same-context counterfactuals (natural experiments), a falsifiable prediction ledger, and an activation skill that teaches when to recall and record.
l123-harness
A project structure for keeping an AI agent’s memory outside the model in three layers: persistent notes, an index, and detailed records. It also provides templates, approval controls, event logs, context-saving procedures, and weekly review tools.
claude-md-management
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
open-knowledge-vault
Create and maintain portable Open Knowledge Format vaults with optional Obsidian and Dataview views.