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AceDataCloud

mcp-webextrator

by AceDataCloud

webextrator_extract

Extract structured content from URLs: product data, articles, or general page details, using JavaScript rendering and optional LLM normalization. Supports sync and async execution.

Instructions

Extract structured content from a web page using the WebExtrator API.

Navigates to the specified URL, renders the page, and extracts structured data
such as product details, article content, or general page information.

Use this when:
- You need to extract structured data from a web page
- You want product details, article content, or general page data
- You need LLM-enhanced semantic normalization of extracted content

Returns:
    By default (async) a JSON envelope with a `task_id` — poll
    `webextrator_get_task` until it reports `finished_at`, then read the
    extracted content from its `response`. With mode="sync", the extracted
    structured content inline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL of the web page to extract content from. Required.
modeNoProcessing mode. Defaults to 'async': returns immediately with a task_id to poll via webextrator_get_task. Pass 'sync' to wait for the result inline (may time out on slow pages).
delayNoExtra delay in seconds after page load before extracting.
cookiesNoCookies to install before navigation. Each cookie is an object with at least 'name' and 'value', plus optional 'domain', 'path', 'expires', 'httpOnly', 'secure', 'sameSite'. Useful for authenticated pages.
headersNoExtra HTTP headers to include with the page request.
timeoutNoTotal timeout in seconds for page load. Default is 30.
enable_llmNoEnable LLM-based semantic normalization for richer structured output. Default is false.
user_agentNoOverride the User-Agent header for the page request.
wait_untilNoPage load wait condition before extracting. Options: 'load', 'domcontentloaded', 'networkidle', 'commit'. Default is 'networkidle'.
bypass_cacheNoSkip the Redis result cache for this request (still writes the fresh result back). Default is false.
callback_urlNoCallback URL for async processing. If provided, the task runs asynchronously and results are sent to this URL when complete.
expected_typeNoHint about expected page type. Options: 'product', 'article', 'general'. Helps the extractor optimize for the content structure.
block_resourcesNoResource types to block during page load to speed up rendering. Options: 'image', 'font', 'media', 'stylesheet', 'xhr', 'fetch'.
cache_ttl_secondsNoOverride the global cache TTL (seconds) for this entry. 0 means do not cache this response. Default is 3600.
wait_for_selectorNoCSS selector to wait for before extracting content.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the async/sync behavior, caching, cookie/header usage, timeout, LLM enrichment, and resource blocking. It does not mention rate limits or authentication requirements, but overall, it's quite transparent for a web extraction tool.

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

Conciseness5/5

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

The description is concise and well-structured. It starts with a clear one-line summary, followed by usage scenarios, and ends with return value explanation. No redundant sentences. Every part serves a purpose.

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?

Given the tool's complexity (15 parameters, 1 required, 100% schema coverage, output schema exists), the description covers all major aspects: navigation, rendering, extraction, async/sync, caching, LLM, and customization options. It is complete enough for an AI agent to use effectively.

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 coverage is 100%, so baseline is 3. The description adds value by explaining the async workflow and polling instructions, which go beyond schema descriptions. It also contextualizes parameters like mode and enable_llm. This extra context justifies a score of 4.

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

Purpose4/5

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

The description clearly states the tool's purpose: extracting structured content from web pages. It lists specific use cases (product details, articles, general content) and distinguishes itself by mentioning both sync and async modes. However, it does not explicitly differentiate from sibling tools like webextrator_render, which may cause slight ambiguity.

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

Usage Guidelines4/5

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

The description includes a 'Use this when' section listing three scenarios, which provides clear guidance. It also explains that async mode returns a task_id to poll using webextrator_get_task, linking to a sibling tool. However, it lacks explicit when-not-to-use guidance or alternatives, which would improve the score.

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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