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.
npx agentmods add skills/rmarquesa/agentmemory-offline/agentmemory-rest-apinpx skills add rmarquesa/agentmemory-offline --skill agentmemory-rest-apigit clone --depth 1 https://github.com/rmarquesa/agentmemory-offlineWhat 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 | $0.00052 | $0.00390 |
| Opus 5 | $0.00026 | $0.00195 |
| Sonnet 5 | $0.00010 | $0.00078 |
| Haiku 4.5 | $0.00005 | $0.00039 |
Grade A, and why
agentmemory-rest-api scanned grade A with 1 finding 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 2d 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 -fsS http://localhost:3111/agentmemory/livez This is a copy
100% identical to agentmemory-rest-api — 0 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
REST is agentmemory's primary surface. MCP is a bridge on top of it. Every memory operation has an HTTP endpoint under http://localhost:3111/agentmemory/*.
Quick start
# liveness
curl -fsS http://localhost:3111/agentmemory/livez
# save
curl -X POST http://localhost:3111/agentmemory/remember \
-H "Content-Type: application/json" \
-d '{"content":"chose JWT refresh rotation","concepts":["jwt-refresh-rotation"]}'
# recall
curl -X POST http://localhost:3111/agentmemory/smart-search \
-H "Content-Type: application/json" \
-d '{"query":"auth token strategy","limit":5}'
Auth
By default localhost is open and no auth is needed. When AGENTMEMORY_SECRET is set, every request needs Authorization: Bearer $AGENTMEMORY_SECRET. See agentmemory-config.
Conventions
- Save returns
201, reads return200, validation errors return400. - Handlers whitelist body fields and drop unknown ones, so passing extra keys is safe but ignored.
- The port is configurable with
--portor--instance; streams, viewer, and engine derive from it.
See also
- agentmemory-mcp-tools for the MCP equivalents.
- agentmemory-config for the port quartet and the secret.
Reference
The full endpoint list with methods lives in REFERENCE.md, generated from src/triggers/api.ts.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 44 lines · 52 tokens per session scan A e7014241e99b
agentmemory-rest-api is a skill published in the GitHub repository rmarquesa/agentmemory-offline (0 stars, last pushed 3d ago), licensed Apache-2.0. It adds 52 tokens to every session and 390 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to agentmemory-rest-api, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
plur-memory
Persistent learning for AI agents. Open engram format. Your agent learns from corrections, remembers across sessions, and transfers knowledge across domains.
plur-session-end
Extract durable learnings at the end of a session. Saves corrections, preferences, and codebase patterns as engrams — nothing ephemeral, nothing sensitive.
plur-memory
Your memory stays on your machine. No cloud, no tracking, no API key. PLUR makes your OpenClaw remember — and shares that memory with every other tool you use.
engraphis-memory
Give the agent durable, scoped, explainable memory across sessions and repositories through the Engraphis MCP tools. Use when you learn a convention, decision, bug cause/fix, or user preference worth keeping; when prior context would help before you answer or act (to avoid re-asking or re-deriving); when asked "why is…
compartmentalize
Sweep this conversation and save everything potentially worth knowing again into Compartment, the encrypted memory vault. Run it before compacting or summarizing so nothing is lost to the summary, or on its own at any point to bank the session.
paxm-setup
Configure paxm for the Claude Code plugin.