mcp server
Boolsai Directory
Indexed ecommerce site directory — vendor lookups, brands by city/market/founder. 10 tools.
Description as published by the maintainer. Source
- version 1.0.0
- slowing
slowing — Most recent push to the repository was 2026-05-19.
What this server can do
19 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
brands_by_founder(founder)- List brands attributed to a founder (from Schema.org Organization markup). Useful for tracking serial DTC founders. Required: founder.
brands_in_city(city)- List indexed brands that publish a physical address in a given city. Sourced from Schema.org Organization JSON-LD. Required: city.
brands_in_market(country)- List indexed brands explicitly serving a country market (via hreflang). Country is a 2-letter ISO code, lowercase. Required: country.
bulk_export(limit, cursor, format, signal_type, signal_value, market_country)- 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. Required: signal_type.
bulk_export_url(format, signal_type, signal_value, market_country)- 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. Required: signal_type.
compare_scans(t1, t2, url)- 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. Required: url.
compare_sites(urls)- 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. Required: urls.
directory_query(city, limit, domain, founder, archetype, signal_type, signal_value, market_country)- 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.
domain_intel(domain)- 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. Required: domain.
find_similar_by_stack(limit, domain, min_shared)- 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. Required: domain.
lookup_id(signal_type, signal_value)- 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. Required: signal_type, signal_value.
operator_cluster(id, limit, domain, signal_type)- 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.
prospect_brief(url, angle)- 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'. Required: url.
similar_sites(url)- Find brands with similar stack archetypes to the given domain. Returns 'sites running similar tech' — useful for benchmarking, prospecting, competitor lookups. Required: url.
site_dossier(url)- 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. Required: url.
sites_using_vendor(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. Required: vendor.
stack_archetype(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. Required: archetype.
subdomain_map(root, limit)- 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). Required: root.
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.
Last successful function declaration observed on . Source: https://directory.boolsai.ai/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://directory.boolsai.ai/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 1 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-05-19 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-05-19 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-05-19 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 19 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | directory.boolsai.ai | |
| mcp endpoint status | ok | The server listed 19 functions when asked. | as of probe | directory.boolsai.ai |
Where to get it
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Live tech-stack scan of any public site — vendors, account IDs, scripts, JSON-LD. 2 tools.
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Boolsai Signals
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Quant-research MCP — tradeable signals from public-company website stack changes. 7 tools.
This record as data
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