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 skills add ThinkfleetAI/memmesh --skill memmesh-cligit clone --depth 1 https://github.com/ThinkfleetAI/memmeshWrote 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/thinkfleetai/memmesh/memmesh-cli)<a href="https://agentmods.dev/skills/thinkfleetai/memmesh/memmesh-cli"><img src="https://agentmods.dev/badge/skills/thinkfleetai/memmesh/memmesh-cli/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/skills/thinkfleetai/memmesh/memmesh-cli"><img src="https://agentmods.dev/badge/skills/thinkfleetai/memmesh/memmesh-cli.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Rogue Agent · line 42 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
- medium MCP Rug Pull · line 9 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 18 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 30 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00164 | $0.00906 |
| Opus 5.5 | $0.00066 | $0.00362 |
| Sonnet 5.5 | $0.00033 | $0.00181 |
| Haiku 4.5 | $0.00016 | $0.00091 |
Grade A, and why
memmesh-cli 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.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MemMesh CLI
The CLI drives the same Rust engine as the hosted platform, but fully local over SQLite — no account, no key, no network. It is also the recommended way to give any MCP-capable agent persistent memory.
Install (one command, multi-tool)
npx @thinkfleet/memmesh install # or: memmesh install
This auto-detects your installed AI tools and, for each, writes the MCP server config and drops the teaching skill:
- Claude Code (
~/.claude.json+~/.claude/skills/) - Cursor (
~/.cursor/mcp.json) - Windsurf
- Codex CLI
Useful flags: --dry-run (preview), --tool <name> (one tool only),
--skill-only / --mcp-only, --force (overwrite existing config).
Verify wiring at any time:
memmesh doctor # checks binary, MCP config, skill presence, hooks
Memory subcommands
memmesh save --type preference --scope user --content "prefers pnpm over npm"
memmesh get <id>
memmesh search --project myapp --query "database" # substring/scoped search
memmesh list --project myapp --limit 20
memmesh migrate # run pending DB migrations
Run the MCP server
Most agents launch this for you via the config the installer wrote. To run it by hand (stdio JSON-RPC 2.0):
memmesh mcp
The server exposes 15 tools — see the memmesh skill for the full list and the
observe/recall usage pattern. Highlights beyond basic CRUD:
memory_predict, memory_build_context, memory_graph_reason,
memory_query_graph, memory_prefetch_related, plus the client-LLM graph
extraction pair (memory_extract_pending / memory_commit_extraction) — the
engine never makes LLM calls; your agent's own model does the extraction.
Local vs hosted
| Local (CLI + MCP) | Hosted (SDK / Mesh Router) | |
|---|---|---|
| Storage | SQLite (~/.thinkfleet-memory/memory.db) |
Postgres, multi-tenant |
| API key | not required | mm-… key or Cognito JWT |
| Surface | 15 MCP tools + CLI | full TS SDK (memmesh-sdk) |
| Sync | CRDT-style bi-temporal push to server (optional) | authoritative |
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 · 93 lines · 164 tokens per session scan A 634da8a143b1
memmesh-cli is a skill published in the GitHub repository ThinkfleetAI/memmesh (405 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 164 tokens to every session and 906 once invoked, about $0.0007 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 2026-08-30.
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memory
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ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…