agentmemory is a persistent-memory system that lets AI coding agents retain and search information across sessions. It connects with several coding agents and MCP clients, storing knowledge with confidence scoring, lifecycle handling, knowledge graphs, and hybrid search. The catalogue contains agentmemory integrations such as skills, hooks, commands, a plugin, and an MCP component.
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.
git clone --depth 1 https://github.com/rohitg00/agentmemoryWrote 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/commands/rohitg00/agentmemory/recall)<a href="https://agentmods.dev/commands/rohitg00/agentmemory/recall"><img src="https://agentmods.dev/badge/commands/rohitg00/agentmemory/recall/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/commands/rohitg00/agentmemory/recall"><img src="https://agentmods.dev/badge/commands/rohitg00/agentmemory/recall.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 | $0.00000 | $0.00184 |
| Opus 5.5 | $0.00000 | $0.00074 |
| Sonnet 5.5 | $0.00000 | $0.00037 |
| Haiku 4.5 | $0.00000 | $0.00018 |
Grade A, and why
recall 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.
What it actually says
Search past session observations and lessons for relevant context. Wrap the memory_smart_search and memory_lesson_recall MCP tools.
Usage
/recall [query]
Instructions
- Call
memory_smart_searchwith the query andlimit: 10(hybrid BM25 + vector + graph search). - Call
memory_lesson_recallwith the same query andlimit: 5(lesson search). - Combine results and present to the user:
- Group by session
- Show type, title, and narrative for each observation
- Highlight high-importance (>= 7) observations
- Show lessons separately with confidence scores
- If no results, suggest 2-3 alternative search terms.
- Never hallucinate results. Only present what the MCP tools actually return.
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 · 20 lines · 0 tokens per session scan A 3b05701dbade
recall is a command published in the GitHub repository rohitg00/agentmemory (29,595 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 184 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
memory
Read-side memory operations on the knowledge graph: search past decisions and patterns, load session context, view decision timelines, render Mermaid graph visualizations. Subcommands: search, load, history, viz, status. Use when finding or reviewing what memory already holds. For storing new knowledge instead, invoke…
compact-prep
Ask the agent to prepare for conversation compaction by updating any relevant state and providing guidance for the compaction agent and to kick off the session there after.
handoff
Write a session handoff document for continuity.
drift-detect
Configuration drift detection command. Finds inconsistencies, orphaned components, and stale content in the Badi system.
sync
Mid-session context refresh command. Keeps context fresh and consistent during work.
claude-flow-memory
Interact with Claude-Flow memory system.