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.
Borrowing it
Nothing to install: this file belongs to mem9-ai/mem9. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mem9-ai/mem9/main/CLAUDE.mdgit 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/instructions/mem9-ai/mem9/claude-md)<a href="https://agentmods.dev/instructions/mem9-ai/mem9/claude-md"><img src="https://agentmods.dev/badge/instructions/mem9-ai/mem9/claude-md/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/instructions/mem9-ai/mem9/claude-md"><img src="https://agentmods.dev/badge/instructions/mem9-ai/mem9/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00005 | $0.00005 |
| Opus 5.5 | $0.00002 | $0.00002 |
| Sonnet 5.5 | $0.00001 | $0.00001 |
| Haiku 4.5 | $0.00001 | $0.00001 |
Grade A, and why
mem9 CLAUDE.md 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.
This is a copy
100% identical to deepseek-harness CLAUDE.md — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
@AGENTS.md
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 · 2 lines · 5 tokens per session scan A 336cc4fbf19b
mem9 CLAUDE.md is an instructions file published in the GitHub repository mem9-ai/mem9 (1,227 stars, last pushed 9d ago), licensed Apache-2.0. It adds 5 tokens to every session, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to deepseek-harness CLAUDE.md, differing in 3 lines, and is treated as a copy.
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