Boolsai Directory

ai.boolsai由 boolsai.ai 发布官方发布者v1.0.0更新于 Oct 24, 2026

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

已验证Streamable HTTP可网页运行数据与分析商业与电商

服务详情

标识符: ai.boolsai/directory
传输: Streamable HTTP
运行时: Web executable
信任: Verified
发布于: Sep 16, 2026

安全提示

MCP 服务会接收对话中的工具调用请求，并可能执行外部操作。启用前请先了解该服务能做什么，并只授予它所需的权限。

注册中心已验证此服务的命名空间属于 boolsai.ai，且该域名同时运行其端点。这可以确认发布者，但并不代表该服务的工具是安全的。

SourceWeft 的检查只涵盖条目是否完整、端点是否响应；不审查服务器的代码，也不审查其工具的行为。

在 README 中添加徽章

向读者展示该 MCP 服务已收录于 SourceWeft，徽章链接到本页。

[![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)

概览

AI 生成的概览

让助手按供应商、账户 ID、城市、市场、创始人或技术栈类型查询一个预索引的电商网站目录。

可以做什么: Boolsai Directory 是一个远程 MCP 服务器，在数万个电商网站的预索引语料上提供十个工具。工具包括 summary、site_dossier、sites_using_vendor、lookup_id、brands_in_city、brands_in_market、stack_archetype、compare_sites、similar_sites 和 brands_by_founder。它可以回答哪些店铺使用某个供应商、哪些品牌位于某城市或市场、哪些网站技术栈相似等问题。
适用场景: 适合竞争情报、代理机构潜在客户研究、电商尽职调查以及商业数据发现，尤其是需要索引查询而非对单个网站做实时扫描的场景。它是 Boolsai 四个服务器之一，其说明会指向另外三个服务器，用于实时扫描、历史模式搜索和信号研究。
运行要求: 远程 streamable HTTP 端点 directory.boolsai.ai，无需安装软件包。README 说明无需身份验证、API 密钥或环境变量。在支持远程 MCP 服务器的客户端中把该 URL 添加为自定义连接器或 MCP 服务器条目，并需要能访问该端点的网络。

安装前请注意

README 称该服务无需认证且公开，因此查询内容以及你查找的网站或供应商会发送到第三方端点。结果是关于公开网站的第三方索引数据，用于决策前应自行核实。未提及凭据、付款或写入操作。

安装

在 SourceWeft 中

打开控制台中的 Boolsai Directory，将其添加到工作区。
为需要使用其工具的对话启用该服务。

Web executable，通过 Streamable HTTP。远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体，或 SourceWeft 对话中。智能体会读取该服务器的安装指南，先向你展示发布者、端点和登录方式，经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/ai.boolsai%2Fdirectory/install.md，并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前，先告诉我它的发布者、端点和登录方式，等我确认。不要把 API 密钥写进命令或我会提交的文件；问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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)