Boolsai Directory

ai.boolsai由 boolsai.ai 發布官方發布者v1.0.0更新於 Oct 24, 2026

Indexed ecommerce site directory — vendor lookups, brands by city/market/founder. 10 tools.

已驗證Streamable HTTP可網頁執行資料與分析商業與電商

服務詳細資訊

識別碼: ai.boolsai/directory
傳輸: Streamable HTTP
執行環境: Web executable
信任: Verified
發布於: Sep 16, 2026

安全提示

MCP 服務會接收對話中的工具呼叫請求，並可能執行外部操作。啟用前請先了解該服務能做什麼，並只授予它所需的權限。

註冊中心已驗證此服務的命名空間屬於 boolsai.ai，且該網域同時執行其端點。這可以確認發布者，但並不代表該服務的工具是安全的。

SourceWeft 的檢查只涵蓋條目是否完整、端點是否回應；不審查伺服器的程式碼，也不審查其工具的行為。

在 README 中新增徽章

向讀者展示該 MCP 服務已收錄於 SourceWeft，徽章連結到本頁。

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/ai.boolsai%2Fdirectory.svg)](https://sourceweft.com/mcp/ai.boolsai%2Fdirectory?utm_source=readme&utm_medium=badge)

概覽

AI 產生的概覽

讓助理依供應商、帳號 ID、城市、市場、創辦人或技術棧類型查詢預先建立索引的電商網站目錄。

可以做什麼: Boolsai Directory 是遠端 MCP 伺服器，在數萬個電商網站的預先索引語料上提供十個工具。工具包括 summary、site_dossier、sites_using_vendor、lookup_id、brands_in_city、brands_in_market、stack_archetype、compare_sites、similar_sites 與 brands_by_founder。可回答哪些商店使用某個供應商、哪些品牌位於某城市或市場、哪些網站技術棧相似等問題。
適用情境: 適合競爭情報、代理商潛在客戶研究、電商盡職調查與商務資料探索，尤其是需要索引查詢而非對單一網站即時掃描的情境。它是 Boolsai 四個伺服器之一，其說明會指向另外三個伺服器，用於即時掃描、歷史樣式搜尋與訊號研究。
執行需求: 遠端 streamable HTTP 端點 directory.boolsai.ai，不需安裝套件。README 說明不需驗證、API 金鑰或環境變數。在支援遠端 MCP 伺服器的用戶端中，將該 URL 新增為自訂連接器或 MCP 伺服器項目，並需要能連線該端點的網路。

安裝前請注意

README 稱此服務無需驗證且公開，因此查詢內容以及你查找的網站或供應商會傳送到第三方端點。結果是關於公開網站的第三方索引資料，用於決策前應自行核實。未提及憑證、付款或寫入操作。

安裝

在 SourceWeft 中

開啟儀表板中的 Boolsai Directory，將其新增到工作區。
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.boolsai%2Fdirectory/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": {
    "boolsai-directory": {
      "type": "http",
      "url": "https://directory.boolsai.ai/mcp"
    }
  }
}

README

Boolsai — MCP server suite

[MCP] [License: MIT] [No-auth]

Stack-intelligence MCPs for AI agents. Live, no-auth, public access to every commerce site's tech stack — every vendor, every account ID, every inline script signature, plus a quant-research signal layer on top.

Built for AI agents doing competitive intel, agency prospect research, ecommerce due diligence, and ad-hoc commerce-data discovery.

This repo contains the Anthropic MCP Registry manifests for the four-server Boolsai suite. The actual servers live at *.boolsai.ai.

The four servers

Server	Connect URL	Tools	What it does
Boolsai Scan	`https://boolsai.ai/mcp`	`boolsai_scan`, `boolsai_scan_paths`	Live tech-stack scan of any public site. Returns every external host, inline script signature, route, vendor, account ID, and JSON-LD organisation block in one response.
Boolsai Directory	`https://directory.boolsai.ai/mcp`	`summary`, `site_dossier`, `sites_using_vendor`, `lookup_id`, `brands_in_city`, `brands_in_market`, `stack_archetype`, `compare_sites`, `similar_sites`, `brands_by_founder`	Pre-indexed directory of tens of thousands of ecommerce sites by vendor, account ID, country, founder, city, archetype.
Boolsai Grep	`https://grep.boolsai.ai/mcp`	`grep_pattern`, `count_pattern`, `sites_with_signal`, `list_signal_types`	Parallel regex search across the R2 corpus of every scan we've ever taken. Use when a signal isn't pre-indexed — discover new vendor patterns, leaked account IDs, niche tracking pixels.
Boolsai Signals	`https://signals.boolsai.ai/mcp`	`universe_summary`, `find_signals`, `test_filter`, `recent_events`, `event_dossier`, `scan_at_date`, `ticker_history`	Quant-research MCP. Hunts for tradeable signals in 316 public-company website stack changes (1,761 events), SPY-benchmarked. Wayback Machine integration. Methodology baked into the `initialize` response.

Each server is independently published to the Anthropic MCP Registry under the ai.boolsai/* namespace (DNS-verified via boolsai.ai).

Why Boolsai

No auth, no key, no rate limit gymnastics. Paste a URL into Claude.ai → Settings → Connectors. Done.
First-party data. Every scan runs live on demand. No third-party feeds, no stale catalogue.
Built for AI consumption. Each server's initialize response includes a detailed instructions block — vendor recognition tips, output schemas, methodology. Agents don't have to guess.
Suite, not silo. Cross-discovery: each server's instructions reference the other three so agents can chain queries (scan → look up in directory → grep historical → test as signal).

Install

Claude Desktop / Claude Code / Cursor

json

{  "mcpServers": {    "boolsai-scan":      { "url": "https://boolsai.ai/mcp" },    "boolsai-directory": { "url": "https://directory.boolsai.ai/mcp" },    "boolsai-grep":      { "url": "https://grep.boolsai.ai/mcp" },    "boolsai-signals":   { "url": "https://signals.boolsai.ai/mcp" }  }}

{  "mcpServers": {    "boolsai-scan":      { "url": "https://boolsai.ai/mcp" },    "boolsai-directory": { "url": "https://directory.boolsai.ai/mcp" },    "boolsai-grep":      { "url": "https://grep.boolsai.ai/mcp" },    "boolsai-signals":   { "url": "https://signals.boolsai.ai/mcp" }  }}

Restart the client. All four servers show up with their tools.

ChatGPT / Claude.ai Custom Connectors

Settings → Connectors → Add custom connector → paste any of the four URLs above. Add all four for the full suite.

One-liner test from a terminal

bash

curl -sS https://boolsai.ai/mcp \  -H 'content-type: application/json' \  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | jq .

curl -sS https://boolsai.ai/mcp \  -H 'content-type: application/json' \  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' | jq .

Example agent prompts

"What's the full tech stack of gymshark.com?" → boolsai_scan({ url: "https://gymshark.com" })

"List ten stores using Klaviyo with their company IDs." → boolsai-directory.sites_using_vendor({ vendor: "klaviyo" })

"Show me sites with window._fs_org (FullStory) in their inline scripts." → boolsai-grep.sites_with_signal({ pattern: "window._fs_org" })

"Find the highest-α tradeable signal in the last 30 days with n ≥ 20." → boolsai-signals.find_signals({ horizon_days: 30, min_n: 20 })

Architecture

                   ┌──────────────────────────┐                   │  AI agent (Claude / etc) │                   └────────────┬─────────────┘                                │ JSON-RPC 2.0 (Streamable HTTP)            ┌───────────────────┼─────────────────────┐            ▼                   ▼                     ▼   boolsai.ai/mcp     directory.boolsai.ai/mcp   grep.boolsai.ai/mcp   (live scanner)     (indexed corpus query)     (raw R2 search)            │                   │                     │            │                   │                     │            ▼                   ▼                     ▼     ┌──────────────────────────────────────────────────────┐     │  R2 corpus (hundreds of thousands of historical scans) │     └──────────────────────────────────────────────────────┘                                ▲                                │ derived                signals.boolsai.ai/mcp  (quant signals from stack changes)

                   ┌──────────────────────────┐                   │  AI agent (Claude / etc) │                   └────────────┬─────────────┘                                │ JSON-RPC 2.0 (Streamable HTTP)            ┌───────────────────┼─────────────────────┐            ▼                   ▼                     ▼   boolsai.ai/mcp     directory.boolsai.ai/mcp   grep.boolsai.ai/mcp   (live scanner)     (indexed corpus query)     (raw R2 search)            │                   │                     │            │                   │                     │            ▼                   ▼                     ▼     ┌──────────────────────────────────────────────────────┐     │  R2 corpus (hundreds of thousands of historical scans) │     └──────────────────────────────────────────────────────┘                                ▲                                │ derived                signals.boolsai.ai/mcp  (quant signals from stack changes)