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/m-t-d-n/agentmemory-codex-windows/agentmemory-mcp-toolsnpx skills add M-T-D-N/agentmemory-codex-windows --skill agentmemory-mcp-toolsgit clone --depth 1 https://github.com/M-T-D-N/agentmemory-codex-windowsWrote 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/skills/m-t-d-n/agentmemory-codex-windows/agentmemory-mcp-tools)<a href="https://agentmods.dev/skills/m-t-d-n/agentmemory-codex-windows/agentmemory-mcp-tools"><img src="https://agentmods.dev/badge/skills/m-t-d-n/agentmemory-codex-windows/agentmemory-mcp-tools.svg" alt="Measured on agentmods" 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 | $0.00051 | $0.00550 |
| Opus 5 | $0.00026 | $0.00275 |
| Sonnet 5 | $0.00010 | $0.00110 |
| Haiku 4.5 | $0.00005 | $0.00055 |
Grade A, and why
agentmemory-mcp-tools 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 5d 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
86% identical to agentmemory-mcp-tools — 5 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.
How it starts
The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agentmemory exposes its full capability set as MCP tools. This skill is the index: it tells you which tool to reach for and where to find exact parameters.
Quick start
Save then recall:
memory_savewith the exact registeredproject,content(the insight),concepts(comma-separated keywords), andfiles(comma-separated paths).memory_smart_searchwith the same exactproject,query, andlimitto retrieve it later. This runs hybrid BM25 plus vector plus graph-expanded search. Useproject: "*"only for a deliberate cross-project read.
Tool families
- Capture:
memory_save,memory_observeflows,memory_compress_file. - Retrieve:
memory_smart_search,memory_recall,memory_file_history,memory_timeline,memory_vision_search. - Sessions and commits:
memory_sessions,memory_commits,memory_commit_lookup. - Knowledge and graph:
memory_lesson_save,memory_lesson_recall,memory_graph_query,memory_relations,memory_patterns,memory_crystallize. - Structured slots:
memory_slot_create,memory_slot_append,memory_slot_get,memory_slot_list,memory_slot_replace,memory_slot_delete. - Governance and health:
memory_governance_delete,memory_audit,memory_verify,memory_heal,memory_diagnose.
Workflow
- Pick the narrowest tool for the task. Prefer
memory_smart_searchfor open recall,memory_recallwhen you already have a focused query,memory_sessionsfor session listings. - Look up exact parameter names and which are required in REFERENCE.md before calling.
- Pass only documented fields. REST handlers whitelist fields and drop unknown ones.
- Keep writes exact-project scoped. Never use
*for a durable write.
See also
- agentmemory-rest-api for the HTTP equivalents.
- agentmemory-config for tool-visibility and feature flags.
- The user-invocable action skills (remember, recall, recap, handoff, forget) wrap the most common tools.
Reference
Full tool table with parameters and the core-set marking lives in REFERENCE.md, generated from source so it never drifts.
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.
- 5d ago First seen · 41 lines · 51 tokens per session scan A 81fd664e645d
agentmemory-mcp-tools is a skill published in the GitHub repository M-T-D-N/agentmemory-codex-windows (2 stars, last pushed 5d ago), licensed Apache-2.0. It adds 51 tokens to every session and 550 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to agentmemory-mcp-tools, differing in 5 lines, and is treated as a copy.
Other skills, from other repositories
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…
slm-recall
Search and retrieve facts, decisions, and past context from SuperLocalMemory. Use when the user asks to recall, find, search, or "what did we decide/say about X". Triggers multi-channel semantic retrieval with reranking; always call before storing anything new.
slm-remember
Capture durable facts, decisions, constraints, and gotchas into SuperLocalMemory. Use when the user says "remember that", "save this decision", "note this constraint", or when a session produces a conclusion worth persisting across sessions. Always recall first to avoid duplicates.
slm-session
Manage SuperLocalMemory session lifecycle — call sessioninit once at the start of every fresh session to load relevant project context and get a sessionid; call closesession when work is meaningfully complete to commit temporal summaries. Correct lifecycle hygiene is what makes SLM's learning loop work.
slm-compress
Compress large text, tool output, or transcripts to reduce context-window usage while keeping the full 1M window intact — call slmcompress(content, mode, reversible, ttlseconds) to shrink content; if the result is lossy a ccrid is returned so you can call slmretrieve(ccrid) later to recover the exact original; always…
slm-scope
Controls memory visibility across profiles — personal (private, default), shared (selected profiles), or global (all profiles on this machine). Default is always personal. Only change scope when the user explicitly asks to share a memory across workspaces. Works with both remember (write scope) and recall (read scope…