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/thinkfleetai/memmesh/memmesh-migratenpx skills add ThinkfleetAI/memmesh --skill memmesh-migrategit 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-migrate)<a href="https://agentmods.dev/skills/thinkfleetai/memmesh/memmesh-migrate"><img src="https://agentmods.dev/badge/skills/thinkfleetai/memmesh/memmesh-migrate.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 | $0.00185 | $0.01094 |
| Opus 5 | $0.00093 | $0.00547 |
| Sonnet 5 | $0.00037 | $0.00219 |
| Haiku 4.5 | $0.00018 | $0.00109 |
Grade A, and why
memmesh-migrate 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.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memmesh-migrate
Move an existing memory setup onto MemMesh with a reviewable, reversible plan.
Canonical sources (fetch first)
- Docs / API mapping: https://docs.memmesh.ai/llms.txt
- Delegate call-site code to:
memmesh-sdk(hosted) /memmesh-cli(local)
Step 1 — audit the incumbent
Detect what's in use and record .memmesh-migration/audit.md:
- Vendor & SDK (Mem0
MemoryClient/Memory, Zep, Letta, LangChain memory, bare Qdrant/pgvector, …). - Call sites — every
add/search/get_all/update/delete. - Scoping — how
user_id/agent_id/run_id/sessionmap today. - Data volume — roughly how many memories, and where they live.
Step 2 — API mapping (cite in the plan)
| Incumbent (e.g. Mem0) | MemMesh equivalent | Notes |
|---|---|---|
client.add(text, user_id=…) |
memory.observe({ text, userId }) |
MemMesh's engine decides what to save — you can stop pre-filtering. |
client.search(q, user_id=…) |
memory.search({ query, userId }) |
Same shape; MemMesh adds scope hierarchy + status lifecycle. |
client.get_all(user_id=…) |
memory.list({ userId }) |
|
client.update(id, text) |
memory.observe(new) + memory.supersede(oldId, newId) |
Correction keeps provenance instead of destructive overwrite. |
client.delete(id) |
memory.delete({ id }) (soft) / hard:true (GDPR) |
|
| user / agent / run scoping | userId / agentId / sessionId (+ projectId, platformId) |
6-level hierarchy. |
| (no equivalent) | lattice.predict / predictTarget, behaviors.discover, context.queryGraph |
This is why you're migrating — calibrated prediction the source can't do. |
Step 3 — data migration
- Export from the incumbent (its export API or a
get_alldump to JSONL). - Transform each record to a MemMesh
observe(preferred — lets the engine re-extract and build the graph) OR amemory.savewith an explicit id when you must preserve exact rows. - Import in batches; keep a checkpoint file so a re-run is idempotent.
- Reconcile — count source vs destination, sample-search for known facts,
write
.memmesh-migration/reconcile.md.
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 · 84 lines · 185 tokens per session scan A 3cfab322aa6d
memmesh-migrate is a skill published in the GitHub repository ThinkfleetAI/memmesh (441 stars, last pushed 10d ago), licensed Apache-2.0. It adds 185 tokens to every session and 1,094 once invoked, about $0.0009 per session on Opus 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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