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Zyte MCP Server

extract_from_http

Extract structured data from a web page using Zyte API automatic (AI) extraction, downloading the raw HTTP response body — no browser. Usually faster and cheaper; fits server-rendered pages; supports device emulation (desktop/mobile). If the page needs JavaScript rendering, or you need browser actions or viewport, use extract_from_browser. Choose the type by page kind — detail types for a single entity's page, list types for per-item summaries from one page, navigation types when crawling, pageContent as the generic fallback, webPageInfo for language only. One type per call. product, article, jobPosting and pageContent results carry metadata.probability — the confidence the page matches the type (below ~0.5 means it might not; a signal, not an error). If unsure between two of those types, make one call per type and keep the higher-probability result; list/navigation/forumThread results have no page-level probability. customAttributes adds caller-defined LLM-extracted fields on top of the requested type; for custom attributes alone use type "pageContent". Supports sessions, cookies, geolocation, and IP type. For raw pages (HTML, screenshots, files) use fetch_page or fetch_http instead. Returns a JSON metadata block (final URL, target HTTP status, optional action results/session), then one JSON block with the extracted data keyed by type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAbsolute http(s) URL of the page to extract from (max 8192 chars). The host must be a domain name, not an IP address.
typeYesThe extraction type to run — one per call. Detail types (product, article, jobPosting, forumThread) suit a page about a single entity; list types (productList, articleList) return per-item summaries from a listing page; navigation types (productNavigation, articleNavigation, jobPostingNavigation) return item/next-page links for crawling; pageContent separates main content from site boilerplate on any page; webPageInfo returns the page language.
deviceNoDevice type to emulate during the HTTP request (default desktop). Browser fetches shape rendering with 'viewport' instead — see extract_from_browser.
ipTypeNoType of IP address to send the request from. Default: Zyte API picks the type that avoids bans for the target site.
sessionIdNoClient-managed session ID — a version 4 UUID you generate. Requests with the same ID reuse the same session (IP, cookies). Sessions expire 15 minutes after creation, after 2 idle minutes, or after 3 bans.
geolocationNoISO 3166-1 alpha-2 country code to route the request from (e.g. 'US', 'DE'); must be a real country code. Default: Zyte API picks a geolocation that avoids bans and locale surprises for the target site.
organizationIdYesRequired. The Zyte organization to attribute this call to (max 100 characters, printable ASCII without spaces). If you do not already have an id, call the user_info tool: it lists the organizations your credential belongs to. IMPORTANT: if it lists more than one, ask the user which to use and wait for their answer — this call is billed to whichever organization you name here, so it is the user's choice to make, not yours. Never guess an id, and never fall back to a default. Once the user has chosen, reuse that id across the session unless they ask for a different organization.
requestCookiesNoCookies to send with the request (max 100). The responseCookies output of a previous fetch_page/fetch_http call can be passed here verbatim.
sessionContextNoServer-managed session context: up to 10 name/value pairs. Zyte API reuses or creates a session per distinct context. Sessions expire after 4 hours or 3 bans.
enableZeroTraceNoKeep the URL and other potentially sensitive request data out of Zyte API's request logs, metrics and stats records for this request. Default false. Use it for sensitive targets; it also leaves Zyte support less to go on when investigating the request.
cookieManagementNoHow cookies are handled: 'auto' (default) uses requestCookies if given, otherwise Zyte API's automatic cookies; 'discard' uses requestCookies if given, otherwise no cookies.
customAttributesNoAd-hoc fields extracted by a Zyte-operated LLM on top of the requested type (max 20 attributes): attribute name to attribute schema. The requested type scopes the page region fed to the LLM. If you only want custom attributes, use type "pageContent".
verifyCertificateNoValidate the target site's TLS certificate and fail with an error instead of extracting from an unverified page. Default false — certificates are not validated. Browser fetches always validate them, so extract_from_browser has no such argument.
sessionContextActionsNoBrowser actions run once to initialize a server-managed session for the given sessionContext (e.g. login steps).

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full duty and does well: it discloses the no-browser HTTP mechanism, performance/cost profile, device emulation support, session/cookie/geolocation/IP support, and a precise output contract (metadata block then a type-keyed JSON block). It even explains probability semantics and that sub-0.5 is a signal not an error. It omits auth/billing and rate-limit behavior, leaving a small gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose is front-loaded in the first sentence, and the dense decision guidance that follows is warranted for a 14-parameter tool with a complex enum. It is long, but nearly every clause provides routing or output semantics rather than padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex, high-stakes extraction tool with no annotations, it covers purpose, alternatives, type selection, tie-breaking, custom attributes, transport options, and return format. An agent has everything needed to select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents parameters. The description nonetheless adds real value beyond the schema, especially for the type enum (detail vs list vs navigation vs pageContent vs webPageInfo), single-type-per-call constraint, and the customAttributes/pageContent interaction.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: 'Extract structured data from a web page using Zyte API automatic (AI) extraction, downloading the raw HTTP response body — no browser.' It immediately distinguishes itself from extract_from_browser and later from fetch_page/fetch_http.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use ('server-rendered pages', 'usually faster and cheaper'), when-not ('if the page needs JavaScript rendering, or you need browser actions or viewport, use extract_from_browser'), and names alternative tools for raw pages (fetch_page/fetch_http). It also routes type selection by page kind with a fallback and a tie-breaking strategy for ambiguous types.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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