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AceDataCloud

mcp-webextrator

by AceDataCloud

webextrator_extract

Extract structured data such as product details, articles, or general page content from any URL. Configure page type, wait conditions, and blocking resources to optimize extraction.

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:
    JSON response containing the extracted structured content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL of the web page to extract content from. Required.
delayNoExtra delay in seconds after page load before extracting.
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'.
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'.
wait_for_selectorNoCSS selector to wait for before extracting content.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description bears full burden for behavioral disclosure. It mentions navigation and extraction but lacks details on safety (e.g., read-only nature), side effects, or rate limits. The description is insufficient for a tool with no annotations.

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 description is reasonably concise and well-structured with purposeful sections ('Use this when', 'Returns'). It is front-loaded with the main purpose. Slightly verbose but acceptable.

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

Completeness4/5

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

Given the tool's complexity (11 parameters, output schema exists), the description provides a good overview of purpose and usage. It covers key aspects like async mode and LLM normalization. Could include more on parameter interactions, but overall adequate.

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

Parameters3/5

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

Schema description coverage is 100%, so baseline is 3. The description adds some context for parameters like expected_type and enable_llm, but it does not substantially enhance understanding beyond the schema.

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 extracts structured content from a web page, listing specific use cases like product details or article content. However, it does not explicitly differentiate from sibling tools like webextrator_render, though the purpose is distinct enough.

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 with clear scenarios. It does not provide explicit when-not-to-use or alternatives, but the context is clear and covers primary use cases.

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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