Signal by StackEnhance MCP Server

How many marketing emails a brand sent in a calendar period, and when, as observed by StackEnhance Signal (ecommerce brands, mostly in Sweden, Norway, Denmark, Finland and Germany). Use for questions like "How many emails did Newport send in August 2026?", "What did Newport send last week?" or "What has X sent recently?". Without a market, a brand tracked in several countries gets one result per market. To compare several brands over the same period, use compare_brands with from and to. Resolve relative dates yourself to YYYY-MM-DD: "last week" is the previous Monday–Sunday, "last month" the previous calendar month, "recently" the last 14 days. Dates are the brand's local calendar dates. The period must start within the last six months (older history is in a Signal account) and may span up to two years. Returns the count; for periods of up to 31 days also the date of each send; and at most two subject lines, only ones already shown on the brand's public StackEnhance page and sent in the period. Every listed send was captured in full; a send without a quoted subject is listed in sends_with_subject_in_signal because its subject is withheld by that limit, not missing. Counts are de-duplicated marketing sends (welcome, birthday and transactional emails excluded). There is no open, click or revenue data. Full campaigns, other subject lines, offers, products and creative analysis are not available through this tool. Cite each result's details_url as the source and as where the full campaigns are.

A brand's email-marketing profile as observed by StackEnhance Signal: market, category, the date Signal first observed it, marketing emails observed in the last 6 months, current frequency (average emails per week over the last 90 days), the date of the latest observed campaign and, for brands Signal has followed 28+ days in SE, NO, DK, FI or DE, its rank in that market by frequency. Use for questions like "How often does Newport email customers?" or "Is IKEA still sending newsletters?". Without a market, a brand tracked in several countries gets one summary per market. For two or more named brands use compare_brands instead of calling this once per brand. Returns aggregates only — no campaign list, subject lines, offers or creative analysis. Cite each result's details_url as the source.

Ecommerce brands StackEnhance Signal tracks in one market, ranked by current email frequency (average marketing emails per week over the last 90 days), optionally within a category such as "Fashion & Apparel" or "Home & Interior". Use for questions like "Which brands email most frequently in Swedish ecommerce?" or to find a brand when the user names a kind of brand ("a Swedish fashion brand"). Rankings are available for SE, NO, DK, FI and DE only; `market` is a country, never a topic. Brands with too little observed data are left out of rankings. To then compare some of the brands (or brands the user named), call compare_brands with their names. Returns brand names, categories and emails per week only. Each brand has a details_url to cite.

Compare 2 to 5 ecommerce brands side by side in ONE call, as observed by StackEnhance Signal: current frequency (average marketing emails per week, last 90 days), emails observed in the last 6 months, the date Signal first observed each brand, the latest campaign date, and each brand's rank in its market when it has one, ordered by frequency. Use this instead of calling get_brand_summary repeatedly when the user names a set of brands: "Compare Mio, IKEA and Westwing", "Who emails more, Boozt or Zalando?", "How does Newport compare with its competitors?". Pass the brand names as the user wrote them. Give `market` (SE, NO, DK, FI, DE or a country name) when the brands are in one country, which is the usual case; a brand tracked in several countries without a market is listed as unavailable with the markets to choose from, never guessed. Optionally give `from` and `to` (YYYY-MM-DD, starting within the last six months) to also count each brand's sends in that period. More than 5 brands: call again with the rest. To discover competitors first, use find_brands. Returns aggregates only: no campaign list, subject lines, offers or creative analysis. There is no open, click or revenue data. Cite each brand's details_url as the source.