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InfinityScrape MCP

InfinityScrape MCP

extract_schema

Extract specific structured fields from a webpage by mapping keys to CSS selectors, turning page content into targeted data.

Instructions

Extract specific structured fields from a webpage using a key-to-CSS-selector dictionary map.

Input Schema

NameRequiredDescriptionDefault
urlYes
schemaYes
use_browserNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden: it never confirms this is a non-mutating read, says nothing about behavior when selectors match nothing, nothing about JS-rendered pages, and nothing about error or partial-result handling. The single sentence describes the shape of the request but not how the tool behaves.

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?

A single front-loaded sentence that packs the verb, resource, and mechanism with no filler or redundancy. Nothing could be removed without losing information.

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

Completeness3/5

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

The output schema is present, so return values need not be explained, and the core extraction concept is conveyed. But for a three-parameter tool with a nested object and zero schema documentation, the definition leaves 'use_browser' unexplained and offers no routing against numerous overlapping sibling extractors.

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 0%, so the description must compensate, and it partially does by explaining that 'schema' is a key-to-CSS-selector map, which clarifies the nested string-to-string object that the schema leaves undocumented. It adds nothing about 'use_browser' (a boolean defaulting to false whose trigger condition is genuinely non-obvious) or about URL expectations.

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?

States a specific verb and resource ('Extract specific structured fields from a webpage') plus the mechanism ('key-to-CSS-selector dictionary map'), which is more than a restatement of the name. It does not distinguish itself from close siblings such as extract_structured, scrape_url, or the specialized extractors (extract_pricing_table, extract_faqs), so an agent must guess which extractor to pick.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance, no mention of when this beats extract_structured or scrape_url, and no prerequisites. The only implicit signal is that the caller supplies CSS selectors, which suggests static markup, but that inference is left entirely to the agent.

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