Find a named page type on a company's own website from its domain, in 11 languages.
The MCP server com.mambabuilt/mcp-page-finder-extractor finds a named page type on a company’s own website by using the site domain. It supports 11 languages, enabling page discovery for different locales. This server is described as a “Page Finder and Extractor MCP Server.”
🛠️ Key Features
Find a named page type using a company website domain
Operate across 11 languages
🚀 Use Cases
Locate specific page types on a target company website (e.g., for extraction workflows)
Handle multilingual sites by language
⚡ Developer Benefits
Uses the website’s domain as the lookup input
Designed for named page-type identification across 11 languages
⚠️ Limitations
Page type lookup is limited to “named page types” on the company’s own website
Language coverage is limited to 11 languages as stated in the description
Give it a company domain and name a page type. It finds that page on the company's own website and returns the URL, the method that found it, and a confidence for that method.
46 page types. Discovery vocabulary in 11 European languages. Optionally reads the page and returns structured fields.
One flat row per input, always, including the ones where nothing was found.
{type}_url is the located page, for example pricing_url.
{type}_found is true, false or null. These are never collapsed.false means the site was read, its link graph and sitemap were searched, and the page is not there. null means not enough was readable to say so.
{type}_method is how it was found: known_url, known_host, homepage_anchor, footer_anchor, section_hop, sitemap or path_guess. Precision differs sharply between them.
{type}_confidence is scored for that method, not blended. Threshold at 0.8 for anything a customer will see. A path_guess never scores above 0.6.
coverage and fetch_status say whether the look completed. Read them before trusting a false.
In locate_and_extract mode the structured fields land in a second findings dataset, one record per field, keyed back by input_key, because eleven filing rows do not fit in one cell.
Billing
Pay per event on Apify credits. Roughly, at the FREE tier: $0.004 per page type located, $0.003 per page extracted, $0.007 per company name resolved, and the standard actor start fee.
A look that happens is billed, including the ones that come back empty, because the work is the same either way. A look that does not happen is not billed: a dead domain, a refusal, or a robots.txt disallow returns found: null and no locate charge.
You are never charged for identity resolution unless you use the companies path.
What this server does and does not do
It reads publicly available pages on the company's own website. It honors robots.txt per host including Crawl-delay, makes one request at a time per domain with a delay, and sends a descriptive user agent that names it. It does not impersonate a browser, does not sign headers, and does not retry to get around a block. Where a page is publicly served but needs JavaScript to read, a browser renders it; a browser is never used against an access control.
Personal data. Two page types can return a named person: contact returns the contact block a company publishes on its own contact page, and about returns leadership names published on its own about page. Only what the company published, no inferred attributes, no lookups elsewhere. Those records carry is_personal_data: true and a lawful_basis, so the whole class filters out with one predicate, or leave contact and about out of pageTypes and none is produced. For a roster of people at a company, use Team Page People Extractor instead.
This server is read only. It starts an actor run and returns the dataset. It writes nothing anywhere else.
Mamba Labs GTM Suite
This server is one of the Mamba Labs MCP servers for go-to-market data, each backed by its own actor on the Apify Store. If you would rather install one package than many, @mambalabsdev/mcp-gtm-suite exposes the suite through a single server.
If you want a roster of people at a company rather than a page on its website, use Team Page People Extractor and Contact Classifier instead. This actor returns a contact block only when it happens to sit on a page you asked it to find.