
Storefront Guard
io.github.maxigirl123由 GitHub 帳號 maxigirl123 發布v0.3.2更新於 Oct 25, 2026
Verifies a merchant storefront is legitimate before an AI agent commits payment.
概覽
一個本機 MCP 伺服器,在 AI 購物代理付款前查核網路商店網域是否可信,回傳信任評分與白話的繼續或阻止建議。
- 可以做什麼
- 驗證商店網域,回傳信任評分、建議(繼續、暫停確認或不要繼續)以及每項扣分的白話原因。查核網域註冊時間與近期變更、SSL 憑證簽發歷史和目前 HTTPS 有效性。交叉比對已知詐騙黑名單、公司登記、法定名稱登錄、網站流量排名、聯邦排除名單與 FDA 執法紀錄。可選擇將交易結果回饋寫入本機日誌。
- 適用情境
- 當助理即將在不熟悉的商家網站完成購買,並希望先取得可解釋的信任訊號時使用。它針對代理購物與結帳流程,而非一般網頁瀏覽。
- 執行需求
- 以 Node.js 18+ 的 npm 套件形式透過 stdio 在本機執行。選用的 API 金鑰 GOOGLE_SAFE_BROWSING_API_KEY、SAM_GOV_API_KEY 與 URLHAUS_AUTH_KEY 可提升涵蓋範圍但非必要。公開查詢需要網路存取。README 另記錄選用的 HTTP、x402 與 REST 模式,需要 PAY_TO_ADDRESS、API_KEYS 等額外變數。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Storefront Guard,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
Fortik
Real-time merchant verification for agentic commerce. A shopping agent calls verify_storefront with a domain before paying, and gets back a trust score with a plain-English verdict the agent can act on — in under two seconds.
Fortik is the trust check AI shopping agents run before checkout. It doesn't ask merchants to register in advance — it gathers evidence directly, in the moment, from independent public sources.
This is the mirror image of merchant-side agent-verification protocols like Visa's Trusted Agent Protocol: those let a merchant confirm an incoming agent is legitimate. Fortik lets the agent confirm the merchant is legitimate before committing payment.
What it checks
- Domain registration age & recent changes — via free public RDAP lookups. A domain registered days ago, or one whose registration data changed in the last two weeks, is a red flag.
- SSL certificate issuance history — via free public Certificate Transparency logs (crt.sh). A cert reissued very recently on an otherwise long-established domain can indicate a takeover or hosting change, even when the domain itself looks old and trustworthy.
- HTTPS validity — does the site currently serve a valid cert at all.
- Known-scam blocklist — URLhaus and Google Safe Browsing.
- Corporate registration — US entity lookup via OpenCorporates.
- Legal name verification — GLEIF entity registry cross-check.
- Web traffic rank — Tranco top-1M ranking.
- Federal exclusions — SAM.gov debarment check.
- FDA enforcement — corroborating signal when other risks are present.
Every deduction from the trust score comes with a plain-English reason in
the reasons array — this is deliberately an explainable heuristic, not a
black-box model.
Setup
Requires Node.js 18+.
Copy .env.example to .env and fill in your keys.
Running it
As a local MCP server (stdio):
As a remote MCP server (streamable HTTP) with x402 payment:
As a pay-per-call x402 HTTP API:
As a REST API (API key auth):
All three servers at once:
Feedback endpoint
Submit outcome data after a transaction to help build training data for future ML scoring:
How to use the recommendation field
Every verification result includes a top-level recommendation string alongside the
numeric trustScore. Agents should branch on it rather than implementing their own
threshold logic against the raw score.
recommendationReason is a one-line plain-English explanation safe to show directly to users.
Pricing
$0.01/call via x402. Set your wallet address in PAY_TO_ADDRESS and network in X402_NETWORK (default: base).
Environment variables
來源:README.md,提交 7989b5f
工具
0版本歷史
1- v0.3.2最新Sep 16, 2026
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