mnemos-setup

mnemos-setup is a skill for Claude Code from unvulcanised-watercress762/mem9. It costs 54 tokens per session (896 once invoked), scanned B, original, Apache-2.0.

A setup guide for mnemos, a persistent memory service for AI agents. It covers deploying the memory server, creating a tenant, and configuring the service for supported agent platforms.

In plain words
What is it for?
Use it to configure mnemo-server and connect mnemos to OpenClaw, Claude Code, or OpenCode.
Why use it?
It explains how to give an agent stored memories that can persist between sessions, including the required server and account configuration.

Skill for Claude Code

Written for Claude Code: Claude Code plugin machinery. Also seen: reads .claude/ paths; mentions Claude Code; built for openclaw.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is MNEMO_DSN="user:pass@tcp(host:4000)/mnemos?parseTime=true" go run ./cmd/mnemo-server.

Good fit Use it to configure mnemo-server and connect mnemos to OpenClaw, Claude Code, or OpenCode.

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Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/unvulcanised-watercress762/mem9
agentmods
npx agentmods add skills/unvulcanised-watercress762/mem9/mnemos-setup

Made for: Claude Code.

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README.md
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Your own site · 80×15
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Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 896 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.00896
Opus 5 $0.00027 $0.00448
Sonnet 5 $0.00011 $0.00179
Haiku 4.5 $0.00005 $0.00090

Measured 11d ago against content hash fd162c79ccb9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade B, and why

mnemos-setup scanned grade B 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 11d 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

Add to `~/.claude/settings.json`:

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s -X POST http://localhost:8080/v1alpha1/mem9s | jq .
skills/mnemos-setup/SKILL.md · 143 lines

How it starts

The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.

mnemos Setup

Persistent memory for AI agents. This skill helps you set up mnemos with any agent platform.

Prerequisites

You need a running mnemo-server instance. See the server README for deployment instructions.

Step 1: Deploy mnemo-server

cd mnemos/server
MNEMO_DSN="user:pass@tcp(host:4000)/mnemos?parseTime=true" go run ./cmd/mnemo-server

Step 2: Provision a tenant

curl -s -X POST http://localhost:8080/v1alpha1/mem9s | jq .
# → { "id": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx", "claim_url": "..." }

Save the returned id.

  • For OpenClaw, this is the value you should store as apiKey (preferred).
  • Legacy OpenClaw config can still store the same value as tenantID, but the plugin will still use v1alpha2.
  • For Claude Code / OpenCode env vars, this remains the tenant ID value used by the current server API.

Step 3: Configure your agent platform

Pick your platform and follow the instructions:


OpenClaw

Add to openclaw.json:

{
  "plugins": {
    "slots": { "memory": "mnemo" },
    "entries": {
      "mnemo": {
        "enabled": true,
        "config": {
          "apiUrl": "http://localhost:8080",
          "apiKey": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
        }
      }
    }
  }
}

Restart OpenClaw. You should see:

[mem9] Server mode (v1alpha2)

Compatibility note:

  • Preferred config: apiKey -> plugin uses v1alpha2 with X-API-Key.
  • Legacy config: tenantID -> plugin treats it as an alias for apiKey and still uses v1alpha2.
  • The underlying value is the same UUID either way.

OpenCode

Set environment variables (add to shell profile or .env):

export MNEMO_API_URL="http://localhost:8080"
export MNEMO_TENANT_ID="xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"

Add to opencode.json:

{
  "plugin": ["mnemo-opencode"]
}

Restart OpenCode. You should see:

[mem9] Server mode (mnemo-server REST API)

Read the full file on GitHub · 143 lines

Changes

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.

  1. 11d ago First seen · 143 lines · 54 tokens per session scan B fd162c79ccb9

Subscribe to this mod's changes

mnemos-setup is a skill published in the GitHub repository unvulcanised-watercress762/mem9 (3 stars, last pushed today), licensed Apache-2.0. It adds 54 tokens to every session and 896 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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