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/michael-denyer/memory-mcpWrote 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/michael-denyer/memory-mcp/bootstrap)<a href="https://agentmods.dev/commands/michael-denyer/memory-mcp/bootstrap"><img src="https://agentmods.dev/badge/commands/michael-denyer/memory-mcp/bootstrap/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/michael-denyer/memory-mcp/bootstrap"><img src="https://agentmods.dev/badge/commands/michael-denyer/memory-mcp/bootstrap.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 | $0.00005 | $0.00137 |
| Opus 5.5 | $0.00002 | $0.00055 |
| Sonnet 5.5 | $0.00001 | $0.00027 |
| Haiku 4.5 | $0.00001 | $0.00014 |
Grade A, and why
bootstrap 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
Seed the memory system from project documentation files.
If a path is provided as $1, use it as root. Otherwise, use current directory.
Use mcp__memory__bootstrap_project tool with:
promote_to_hot: trueto make memories instantly available- Auto-detects: CLAUDE.md, README.md, CONTRIBUTING.md, ARCHITECTURE.md
After bootstrapping, show:
- Number of files processed
- Number of memories created
- Any errors encountered
If hot cache was empty, this is especially important for getting started quickly.
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 · 5 tokens per session scan A a9122f335529
bootstrap is a command published in the GitHub repository michael-denyer/memory-mcp (12 stars, last pushed 5d ago), licensed MIT. It adds 5 tokens to every session and 137 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-08-31.
Other commands, from other repositories
remember
Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations. Use when something worth persisting across sessions was just learned or decided. To search or read existing memory, invoke memory; to debug retrieval internals…
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…
dream
Nightly memory consolidation: prunes stale entries, merges duplicates, resolves contradictions, rebuilds the MEMORY.md index. Use when memory files accumulated over many sessions need cleanup. New decisions get stored by remember; searches run through memory; internals live in memory-fabric.
set-context
Set the client context so all subsequent analyses are automatically tailored — store client name, industry, size, geography, and key facts.
recall
Recall memories with filtering and search.
query
Structured frontmatter queries using yq.