ai.boolsai/grep

Tools

• brands_by_founder

  List brands attributed to a founder (from Schema.org Organization markup). Useful for tracking serial DTC founders.

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• brands_in_city

  List indexed brands that publish a physical address in a given city. Sourced from Schema.org Organization JSON-LD.

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• brands_in_market

  List indexed brands explicitly serving a country market (via hreflang). Country is a 2-letter ISO code, lowercase.

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• bulk_export

  Paginated bulk export of indexed sites matching a filter. Returns up to 1000 rows per page in CSV or JSONL format with a cursor for continued pages. Use this when an agency needs an outbound prospect list (e.g. all sites using Klaviyo in the US) for CRM import. The full row count is also returned so you can size the export.

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• bulk_export_url

  Returns a streaming-export URL for the same filter as bulk_export. Useful when the agency wants to pull 50K rows in one shot via curl/HTTP pipe instead of paginating the MCP. The URL is public, no auth, returns NDJSON or CSV with HTTP chunked-transfer streaming. Use bulk_export when N<1000; use this for bigger exports.

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• compare_scans

  Compare two historical scans of the same URL to surface stack changes. Returns added/removed/changed vendors, account IDs, and inline-script signals between scan A and scan B. Use this for competitor watch — 'what did patagonia.com just deploy?'. If t1/t2 are omitted, compares oldest vs newest available scan.

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• compare_sites

  Side-by-side stack comparison of 2-5 domains. Returns each site's vendors, account IDs, brand info, markets — and which signals are shared / unique per site. Good for 'compare X.com vs Y.com' or competitive teardowns.

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• count_pattern

  Same as grep_pattern but returns only the count of matching sites. Faster — no per-match serialization. Useful for sizing 'how many sites use X' before doing a full grep.

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• directory_query

  Unified query against the Boolsai Directory. One tool to rule the other lookups. Pass any combination of: signal_type+signal_value, domain, market_country, archetype, founder, city. Returns matching sites + their key signals. Prefer this over the granular tools when you have multiple filter conditions to AND together.

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• domain_intel

  Free DNS/WHOIS enrichment for a single domain. Returns: email host (Google Workspace / Microsoft 365 / etc. — derived from MX records), DNS provider (Cloudflare / Route 53 / GoDaddy / etc.), CDN provider, registrar, domain age (registered/expires). High-signal outbound data — 'they use Google Workspace + Cloudflare DNS + registered with GoDaddy' tells you a lot about org size + sophistication. Results cached 24h. Free — uses Cloudflare DoH + public RDAP.

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• find_similar_by_stack

  Find sites with the most-similar vendor stack to a given domain using Jaccard similarity over the full vendor set (not just archetype labels). Returns the top N matches with similarity scores. Use this when stack_archetype labels are too coarse and you want 'show me 20 brands running an almost-identical stack to liquiddeath.com'. More accurate than similar_sites for niche stacks.

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• grep_pattern

  Run a JavaScript regex across every scan we've ever taken. Returns matching site URLs (and optional snippets). Best for ad-hoc discovery of patterns NOT already extracted into id_index. Pass narrowing filters (vendor, tld, since) to keep scan volume manageable. Default returns URLs only — set with_snippets=true if you also want the matched JSON context.

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• list_signal_types

  Returns the full catalog of signal_types currently present in id_index, with counts of unique values and unique domains for each.

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• lookup_id

  Cross-reference any tenant-unique account ID across the index. Useful for 'who else shares this GTM container / Klaviyo company / Sentry org / Meta pixel ID?'. Signal types: gtm_container, ga4_measurement, ga_ua, klaviyo_company_id, meta_pixel_id, shopify_shopid, myshopify_slug, hotjar_id, intercom_app_id, hubspot_portal, klaviyo_subscriber, tiktok_pixel, stripe_pk_live, sentry_dsn_org, tealium_tenant, optimizely_project, mparticle_workspace, segment_writekey, abtasty_account, fullstory_org, pendo_account, intellimize_acct, webflow_site_id, dynamic_yield, wunderkind_site, elevar_id.

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• operator_cluster

  Find every domain sharing a tenant-unique ID — the most powerful single signal in Boolsai. Given a Stripe pk_live key, Sentry DSN org, Klaviyo company_id, mParticle workspace, GTM container, GA4 measurement, Shopify shop_id, or other tenant ID, returns every domain we've seen using the SAME ID. This surfaces multi-brand operators, holding-company portfolios, sister brands sharing infrastructure, agency-managed clusters. No competitor (BuiltWith, Wappalyzer, etc.) can do this — they only see external hostnames, not the tenant-unique IDs leaked client-side. Use this when you want to discover the actual operator behind a brand, or expand a single brand into its full portfolio.

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• prospect_brief

  ONE-CALL PROSPECT BRIEF for agency outbound — runs four sub-queries against the live indexed data: (1) full dossier of the prospect's stack, (2) sister brands sharing tenant IDs (operator cluster), (3) 3-5 similar-stack competitors, (4) structured 'pitch angles' calling out concrete gaps an agency could pitch on (missing consent, no SST, outdated vendors, broken Schema.org, multiple GTM installs). Saves a strategist 20 min of manual cross-referencing per prospect. Use this whenever the user asks 'tell me about prospect.com'.

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• similar_sites

  Find brands with similar stack archetypes to the given domain. Returns 'sites running similar tech' — useful for benchmarking, prospecting, competitor lookups.

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• site_dossier

  Full intel dossier for a single domain: detected vendors grouped by category, account IDs (GTM, GA4, Klaviyo company_id, Shopify shop_id, Meta pixel, Sentry org, Tealium tenant, Stripe pk_live, etc.), brand identity (name, founder, city, employees, social handles), international markets, external host list, and likely operator-cluster siblings. Use for any 'what's running on X.com?' query.

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• sites_using_vendor

  List indexed sites detected using a specific vendor (e.g. 'klaviyo', 'yotpo', 'elevar', 'gorgias', 'rebuy'). Vendor slug is lowercase, underscore-separated. Returns domain list with brand names where known.

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• sites_with_signal

  Return sites that have a known signal_type=signal_value pair in id_index. MUCH faster than grep_pattern — uses pre-indexed D1 lookup. Use this whenever the signal_type is in the list (see instructions). Examples: sites_with_signal(signal_type='vendor', signal_value='mparticle_workspace') ← won't work, that's an ID type, use sites_with_signal(signal_type='mparticle_workspace') WITHOUT signal_value to list all values + their domains.

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• stack_archetype

  List brands matching a stack archetype. Valid slugs: headless-shopify, classic-shopify-dtc, server-side-tagged, personalisation-heavy, pixel-stacked, multi-region, woocommerce-stores, magento-stores, bnpl-enabled, headless-cms.

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• subdomain_map

  Every subdomain of a given root domain we've ever scanned. Reveals storefront topology — where the checkout actually lives, regional storefronts, B2B portals, internal admin domains, asset CDNs. Output groups subdomains by their primary vendor where known. Use this to (a) find the right path to scan for an audit (sometimes the checkout is on us.checkout.brand.com not brand.com), (b) spot enterprise topology (multi-region Plus stores), (c) discover sister surfaces (community, ambassador, careers, etc).

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• summary

  Global stats for the Boolsai directory: how many sites are indexed, signal types covered, top vendors, most-changed companies. Use at the start of a session to ground what's available.

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Tool count and median score across every tool in this server’s corpus — honest in a way a single cherry-picked tool’s badge wouldn’t be.

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