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 LorenzoLombardi111/factory-mcpvet --skill mcpvetgit clone --depth 1 https://github.com/LorenzoLombardi111/factory-mcpvetWrote 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/lorenzolombardi111/factory-mcpvet/mcpvet)<a href="https://agentmods.dev/skills/lorenzolombardi111/factory-mcpvet/mcpvet"><img src="https://agentmods.dev/badge/skills/lorenzolombardi111/factory-mcpvet/mcpvet/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/lorenzolombardi111/factory-mcpvet/mcpvet"><img src="https://agentmods.dev/badge/skills/lorenzolombardi111/factory-mcpvet/mcpvet.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 | $0.00086 | $0.00535 |
| Opus 5 | $0.00043 | $0.00267 |
| Sonnet 5 | $0.00017 | $0.00107 |
| Haiku 4.5 | $0.00009 | $0.00053 |
Grade A, and why
mcpvet scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sS --max-time 90 -X POST https://mcpvet.com/api/scan \ What it actually says
MCPVet — vet agent extensions before you install them
You scan untrusted agent extensions through the hosted MCPVet API and report a clear safety verdict. All analysis runs server-side; you only send the target and present the result. No credentials, no local file access.
How to scan
Run one request. The target may be a GitHub repo URL, an npm package name, or pasted skill/manifest text.
curl -sS --max-time 90 -X POST https://mcpvet.com/api/scan \
-H 'Content-Type: application/json' \
-d "$(jq -nc --arg t "<TARGET>" '{target:$t}')"
(If jq is unavailable, build the JSON body carefully so the target string is
properly escaped.)
How to report the result
The API returns JSON:
{
"ok": true,
"overall_risk": "clean|low|medium|high|critical",
"summary": "plain-English risk summary",
"files_scanned": 42,
"findings": [{"severity":"...","label":"...","file":"...","line":12}],
"report_url": "https://mcpvet.com/r/XXXX"
}
Present it concisely:
- Lead with the risk grade and a one-line plain-English takeaway.
- 🟢 clean/low · 🟡 medium · 🟠 high · 🔴 critical
- List the notable findings (
severity,label,file:line). - Give a clear recommendation: safe to install / review first / do not install.
- Always include the
report_urlso the user can share or dig deeper.
If ok is false, relay the message field. Never claim an extension is safe
if the scan failed — say the scan could not complete.
A clean MCPVet verdict reduces but does not eliminate risk: it reflects static + AI review of fetched source, not runtime behavior. Say so when it matters.
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.
- 11d ago First seen · 59 lines · 86 tokens per session scan A 4d169493b776
mcpvet is a skill published in the GitHub repository LorenzoLombardi111/factory-mcpvet (0 stars, last pushed 2mo ago), licensed MIT. It adds 86 tokens to every session and 535 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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