ARC: agent checkout reachability

ai.arcreport由 arcreport.ai 發布官方發布者v2.2.0更新於 Oct 27, 2026

Free, no sign-in MCP: can AI agents reach checkout at a store? Try: Use ARC to check allbirds.com

發布方自己的服務:ARC (arcreport.ai): can an agent reach checkout?

已驗證Streamable HTTP可網頁執行網頁搜尋與抓取安全與監控商業與電商

概覽

AI 產生的概覽

ARC 是託管的 MCP 伺服器,讓助理依帶日期的已存檢查結果,判斷 AI 代理能否在某个網路商店走到結帳。

可以做什麼
  • 依商店網域查詢已儲存的結帳可達性,或依平台、協定、類別尋找代理可結帳的商店
  • 回報代理在某商店的進展,讀取已儲存的商品資料、退換貨與運送政策檢查,以及 Google 代理結帳就緒檢查
  • 對商品網址執行就緒檢查,並取得結果、進度、評分、各代理明細與截圖
  • 詢問基準代理人物設定對品牌的看法,並取得讓商店可被觸及、可被購買的具體改善建議
  • 建立、列出、修改、暫停、恢復並立即執行商店網址的排程監控,並彙整趨勢與退步警示
適用情境
適合助理在購物或測試電商流程前,先確認代理能否到達某商店的結帳;也適合商家長期追蹤並改善代理就緒度。
執行需求
遠端 Streamable HTTP 端點,無需安裝。讀取已存檢查與回報結帳嘗試不需登入;商店卡片、就緒檢查、改善建議、人物設定問答與監控需要登入 ARC 工作區。未宣告任何 API 金鑰或環境變數。
安裝前請注意
多項工具需要登入並對工作區生效。監控會依排程執行,run_monitor_now 會消耗一次掃描額度,應僅在使用者明確要求時呼叫。回報內容在足夠多獨立貢獻者確認前保持私密,且不得包含電子郵件、電話、街道地址、卡號、IP 位址或私有主機。結果僅供參考、帶日期且可能過期;缺少結果不等於否定。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 ARC: agent checkout reachability,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/ai.arcreport%2Fmcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "arc-agent-checkout-reachability": {
      "type": "http",
      "url": "https://www.arcreport.ai/api/mcp"
    }
  }
}

README

ARC: Agentic Report Card

ARC is the free, neutral record of which online stores AI agents can actually reach checkout at, with dated evidence.

Website: https://www.arcreport.ai

This repo holds ARC's public MCP connector metadata and setup instructions. ARC is a hosted service, so there is nothing to install or run.

Quick start: precheck (free, no sign-in, CC BY 4.0)

Before your agent tries a store, ask ARC whether agents can reach checkout there:

bash
curl "https://www.arcreport.ai/api/precheck?url=https://allbirds.com"

Real response (trimmed, 14 Oct 2026):

json
{"host":"allbirds.com","known":true,"reachable_checkout":true, "rails":[{"name":"UCP","status":"valid"},{"name":"ACP","status":"not_found"},          {"name":"MCP","status":"yes"},{"name":"Checkout WebMCP","status":"detected"}], "blockers":[],"confidence":"high","last_checked":"2026-10-13T09:47:13.000Z", "stale":true,"source":"ARC (arcreport.ai)","licence":"CC BY 4.0"}

reachable_checkout is based on ARC's last saved check. It does not mean an agent completed checkout. Check last_checked and stale before relying on it. Contact: [email protected] (ARC).

Advisory only, not a guarantee. Missing data or known:false is not a no.

Endpoints

WhatURLRegistry name
MCP connector (store checks)https://www.arcreport.ai/api/mcpai.arcreport/mcp
Ask connector (stores, protocols, submissions)https://www.arcreport.ai/api/askai.arcreport/ask

Both use the Streamable HTTP transport and are listed in the official MCP Registry. Reading saved checks (check_store, find_stores) and reporting a checkout attempt (report_checkout) need no sign-in.

Other ways in

Setup

Claude Code

bash
claude mcp add --transport http arc https://www.arcreport.ai/api/mcp

Claude Desktop / claude.ai

Settings → Connectors → Add custom connector → URL https://www.arcreport.ai/api/mcp.

ChatGPT

Settings → Apps & Connectors → Advanced → Developer mode → Create connector → URL https://www.arcreport.ai/api/mcp.

Cursor (~/.cursor/mcp.json)

json
{ "mcpServers": { "arc": { "url": "https://www.arcreport.ai/api/mcp" } } }

VS Code (.vscode/mcp.json)

json
{ "servers": { "arc": { "type": "http", "url": "https://www.arcreport.ai/api/mcp" } } }

Cline (cline_mcp_settings.json)

json
{ "mcpServers": { "arc": { "type": "streamableHttp", "url": "https://www.arcreport.ai/api/mcp" } } }

Swap in https://www.arcreport.ai/api/ask to use the Ask connector.

Files

  • server.json: registry entry for ai.arcreport/mcp (copies of both entries in server.mcp.json and server.ask.json)
  • glama.json: Glama directory metadata

How ARC reports results

Every result is dated and labelled by source: agent-reported, ARC-tested up to payment, or a verified order. A missing result never counts against a store.

License

Repo contents: MIT. ARC data: CC-BY-4.0.

來源:README.md,提交 629c197

工具

19

check_store

Check if an AI agent can reach checkout on a store before trying. Call this with a store domain, such as allbirds.com. Returns the saved checkout evidence, or not checked yet when ARC has no saved check. Free, no login, no new scan, and no fetch of the store. A missing field says "not recorded" and is not a zero. Results are advisory. ARC stops before payment.

輸入參數domain必填

find_stores

Find stores where a saved check shows an AI agent can reach checkout. Filter by platform, protocol, or category. With no filters, returns the most recently checked of those stores and labels the result default: no filters given. A missing result is not counted against a store. No login and no new scan. Results are advisory. ARC stops before payment.

輸入參數limitcategoryplatformprotocol

report_checkout

Report how far one agent got at one store. Free, no login. Omit contributor_key and ARC issues one. Emails, phones, street addresses, card numbers, IP addresses, and private hosts are rejected. The report stays private until 3 independent contributors with a day-old key, or enough reputation, agree within 14 days. A blocked outcome also waits for ARC's free HTTP recheck. Same as POST /api/outcomes.

輸入參數blocker必填timestamp必填agent_name必填agent_family必填store_domain必填furthest_step必填contributor_keystore_error_text

get_store_hub

[Requires sign-in] Look up a free ARC store card by host. Includes saved measurements and brand_claim ownership metadata. Brand statements are not measured by ARC; claims never change measured scores.

輸入參數host必填

google_checkout_readiness

[Requires sign-in] Read saved public Google agentic checkout readiness checks for a store. Free; no new scan or paid calls. Merchant Center feed eligibility cannot be checked from outside. Not Google approval or certification.

輸入參數host必填

product_data_check

Free latest saved product data and return/shipping policy check from the store's pages and structured data. Reads history only; no store fetch or model call. A missing result is not a zero.

輸入參數urlhost

can_agent_checkout

[Requires sign-in] Call when you need a saved checkout-link check for any public store URL, not only Index brands. Saved HTTP checkout check for a public homepage or product URL: catalog, product, checkout link, UCP profile, blocks, and one fix. No model call, payment, or browser scan. Uses ARC's last check (cached up to 24 hours). A missing result is unknown, not a no. A checkout link means reach checkout, not a completed order. Results are advisory. ARC stops before payment.

輸入參數url必填

check_agent_readiness

[Requires sign-in] Check whether personal AI agents can reach a product URL, understand it, and reach checkout. Runs ARC's readiness check: crawler access, whether an agent can answer a shopper's questions from the page, and personal shopping agents trying to add to cart or reach checkout. Returns a check id — poll get_readiness_result (about 30–60 seconds). This does not ask what agents think of the brand; use ask_agents_about_brand for that.

輸入參數url必填task

get_readiness_result

[Requires sign-in] Get a readiness check by id. While running, reports progress. When complete, reports whether personal agents could reach the page, understand it, and reach checkout, plus the wall, concrete next steps, a directional score, a per-agent breakdown, and screenshots. Calling this again with the same id redisplays the result and does not start a new check. Never re-run check_agent_readiness just to see the screenshots again.

輸入參數id必填

list_readiness_checks

[Requires sign-in] List this workspace's recent readiness checks (newest first) — each store, its score, status, and id. Use an id with get_readiness_result to reopen a check.

無需輸入參數。

ask_agents_about_brand

[Requires sign-in] Ask benchmark personal-agent personas what they think of a brand and whether they would recommend it for a category. Personas: Muse-style, Instinct-style, Grok Bot-style, OpenAI dots-style, and OpenClaw-style. This tool uses benchmark personas, including the Grok Bot-style persona; these are not live consumer-product sessions. It is not the real Grok read-back on a scan and it is not the agent-rails HTTP check. What Grok tells shoppers on a scan is a real model call via API, checked against the store's pages, not the consumer Grok app. All five cart attempts, Grok included, are ARC browser cart tests. Returns, per persona: mentioned, recommended, which competitors were recommended instead, sentiment, and short quotes, plus next steps. Limited to 8 runs per workspace per day and 12 per network. Free workspaces also share a site-wide daily cap so unpaid runs cannot drain the model budget.

輸入參數brand必填category必填store_url必填competitors

get_fixes

[Requires sign-in] Concrete next steps to get recommended by personal agents and to become reachable, understandable, and buyable. Pass a readiness check id and/or the brand, category, store URL, and competitors that were recommended instead. Uses the check's evidence when an id is given. Does not start a new check.

輸入參數brandscan_idcategorymentionedstore_urlrecommendedcompetitors_recommended

bulk_create_monitors

[Requires sign-in] Set up scheduled monitoring for one or more store URLs (the 'set up monitoring' flow). Validates each URL and rejects invalid/private/internal ones. GUIDED FLOW: first ask the user for the URLs (paste a list or a CSV), then the frequency (daily/weekly/monthly, default weekly). Every plan runs the core panel of personal shopping agents — no picking needed. Call once without confirmed=true to preview the exact setup and scan-credit estimate, read that summary to the user, and only after the user explicitly says yes call again with confirmed=true to create the monitors. Each scheduled run uses one scan credit. Every run emails who reached the cart, who stopped or started, the stuck step, and the fix. Weekly is what the plans include; daily only fits when the plan's scan allowance covers it.

輸入參數urls必填depthconfirmedfrequency

list_monitors

[Requires sign-in] List the workspace's monitors — each store re-checked on a schedule for whether personal agents can still reach it and its checkout. Includes cadence, status, last score, next run, and the monitor id.

無需輸入參數。

monitor_summary

[Requires sign-in] Overview of whether monitored stores are still buyable by personal agents: latest score, trend, status, next run, and recent regression alerts.

無需輸入參數。

update_monitor

[Requires sign-in] Change a monitor's cadence (daily/weekly/monthly) or label. Use the monitor id from list_monitors.

輸入參數id必填labelfrequency

pause_monitor

[Requires sign-in] Pause a monitor so it stops running on schedule (its history is kept). Use the monitor id from list_monitors.

輸入參數id必填

resume_monitor

[Requires sign-in] Resume a paused monitor.

輸入參數id必填

run_monitor_now

[Requires sign-in] Run a monitor's scan immediately (off-schedule) to establish or refresh its baseline. Consumes one scan credit — only call when the user explicitly asks to run now. Use the monitor id from list_monitors.

輸入參數id必填

版本歷史

2
  1. v2.2.0最新Oct 13, 2026
  2. v2.1.0Oct 12, 2026

評分

已滿足適用檢查項的 100%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分

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