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/AGENTS.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/agents-md)<a href="https://agentmods.dev/instructions/mem9-ai/mem9/agents-md"><img src="https://agentmods.dev/badge/instructions/mem9-ai/mem9/agents-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/agents-md"><img src="https://agentmods.dev/badge/instructions/mem9-ai/mem9/agents-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 | $0.03034 | $0.03034 |
| Opus 5.5 | $0.01214 | $0.01214 |
| Sonnet 5.5 | $0.00607 | $0.00607 |
| Haiku 4.5 | $0.00303 | $0.00303 |
Grade A, and why
mem9 AGENTS.md scanned grade A with 2 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- `curl` calls use explicit timeouts. Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
python3 -c 'from pathlib import Path; import re, subprocess; text = Path("AGENTS.md").read_text(); paths = re.findall(r"`([^`]+/AGENTS\.md)`", text); tracked = set(subprocess.check_output(["git", "ls-files", "*AGENTS.md" How it starts
The opening of the file, as written. The whole thing — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What this repo is
mnemos is shared, cloud-persistent memory for coding agents. The core system is a Go REST server backed by TiDB/MySQL, plus four agent integrations, a standalone CLI, and a small Astro site.
Cross-repo relationship: mem9 and mem9-node
mem9-nodeis a sibling repository at../mem9-node. It is not a directory inside this repo.dashboard/appin this repo is the frontend half of the dashboard product. In day-to-day discussion, "the dashboard backend" usually refers to code inmem9-node, especiallyapps/apiandapps/worker.dashboard/app/src/api/analysis-client.tscallsmem9-nodeendpoints forv1/analysis-jobs,v1/deep-analysis/*, and taxonomy/deep-analysis workflows.mem9-node/apps/api/src/mem9-source.service.tsdepends on this repo's Go API as the mem9 source of truth. ItsMEM9_SOURCE_API_BASE_URLdefaults tohttp://127.0.0.1:8080/v1alpha2/mem9s.dashboard/app/src/api/provider-http.tsstill sends the dashboard's standard/your-memory/api/...data requests to this repo's Go server (/v1alpha2/mem9s/...) usingX-API-KeyandX-Mnemo-Agent-Id.- When a task touches dashboard UI and backend behavior together, inspect both repos before assuming the implementation belongs only under
server/in this repo.
High-level modules
| Path | Role |
|---|---|
server/ |
Go API server, business logic, TiDB SQL, tenant provisioning, runtime usage |
cli/ |
Standalone Go CLI for exercising mnemo-server endpoints |
dashboard/app/ |
React dashboard SPA; frontend half of the dashboard product |
openclaw-plugin/ |
OpenClaw memory plugin (kind: "memory") |
opencode-plugin/ |
OpenCode plugin (@mem9/opencode) |
claude-plugin/ |
Claude Code plugin (hooks + skills) |
codex-plugin/ |
Codex plugin (hooks + $mem9:* skills) |
dsh-plugin/ |
DeepSeek Harness DSH/Cordis bundle |
docs/design/ |
Architecture/proposal notes and design drafts |
site/ |
Astro static site — deployed to Netlify from main branch |
e2e/ |
Live end-to-end scripts against a running server |
benchmark/MR-NIAH/ |
Benchmark harness for OpenClaw memory evaluation |
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 · 253 lines · 3,034 tokens per session scan A 12177ba456f2
mem9 AGENTS.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 3,034 tokens to every session, about $0.0121 per session on Opus 5.5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.