Scrapingdog MCP Server

Web Scraping API

web_scrape

Scrape any URL with rotating proxies and optional JavaScript rendering, returning HTML or AI-extracted data.

Instructions

General-purpose web scraper. Fetches any URL through Scrapingdog's rotating proxies with optional JavaScript rendering, premium proxies, geo-targeting, and AI-based extraction. Returns the page HTML (or extracted data).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "web_scrape"
  }
}

Input Schema

Name	Required	Description
`url`	Yes	The absolute URL of the page to scrape.
`wait`	No	Milliseconds to wait after page load before capturing (only with dynamic=true).
`country`	No	Two-letter ISO country code for the proxy geo-location (requires premium). (API default: us)
`dynamic`	No	Set true to render JavaScript with a headless browser. Costs more credits. (API default: false)
`premium`	No	Set true to use premium (residential) proxies for hard-to-scrape sites. (API default: false)
`ai_query`	No	Natural-language instruction to extract specific data from the page via AI.
`markdown`	No	Return the page content converted to clean markdown instead of raw HTML. (API default: false)
`session_number`	No	Reuse the same proxy IP across requests by passing a stable integer.
`ai_extract_rules`	No	JSON string of field->instruction rules for structured AI extraction.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Aug 1, 2026

TDQS

A3.9/5.0

Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently mentions the use of Scrapingdog's rotating proxies, optional JavaScript rendering, premium proxies, geo-targeting, and AI-based extraction, as well as the return type (HTML or extracted data). However, it does not cover error handling, rate limits, or limitations like login-protected pages, but the provided detail is substantial.

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 two sentences, front-loaded with the core purpose, and every phrase adds value. It efficiently conveys the tool's scope, mechanisms, and output without wasted words.

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?

Given the complexity of 9 parameters and no output schema, the description provides a high-level overview but lacks guidance on parameter interplay (e.g., wait only with dynamic), cost implications beyond dynamic's mention in schema, and return format nuances. The schema partially compensates, but the description alone is not fully complete for a tool of this complexity.

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 parameters are fully documented in the schema. The tool description adds no additional parameter semantics beyond what the schema already provides, making this a baseline score.

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?

The description clearly states the tool's function: fetching any URL via a general-purpose web scraper with rotating proxies and returning HTML or extracted data. The verb 'fetches' and resource 'any URL' are specific, and it distinguishes itself from specialized siblings like google_search and screenshot by being general-purpose.

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

Usage Guidelines3/5

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

The description implies the tool is for scraping arbitrary URLs but does not explicitly state when to use it instead of specialized tools like google_search or screenshot. There are no exclusions or alternative suggestions, leaving usage context to be inferred.

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