Scrapingdog MCP Server

Universal Search API

universal_search

Scrapes major search engines and returns unified organic results. Specify query, country, and language for geo-targeted searches.

Instructions

Single endpoint that scrapes major search engines and returns unified organic results.

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": {
      "query": "<query>"
    },
    "name": "universal_search"
  }
}

Input Schema

Name	Required	Description
`query`	Yes	Search query.
`country`	No	Two-letter ISO country code to geo-target results (e.g. us, gb, in, de). (API default: us)
`language`	No	Result language code (e.g. en, es, fr, de). (API default: en)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Aug 1, 2026

TDQS

B3.3/5.0

Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions scraping but omits critical details like potential rate limiting, blocking risks, or that 'unified organic results' may aggregate data from multiple engines without clear provenance. The minimal disclosure is insufficient for a tool that performs web scraping.

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 a single concise sentence that immediately conveys the core function. Every word adds value, and it is front-loaded with 'Single endpoint', making the purpose clear without unnecessary elaboration.

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 lack of output schema and annotations, the description provides only a basic understanding. It does not mention that the tool aggregates across multiple engines, which is essential context for an agent comparing it to single-engine tools. The description is adequate but leaves gaps around behavior and scope.

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?

The input schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds no parameter-specific semantics, but the schema already provides adequate meaning for query, country, and language.

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 scrapes major search engines and returns unified organic results, using a specific verb ('scrapes') and resource ('major search engines'). This distinguishes it from sibling tools like google_search or bing_search, which target a single engine.

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?

No guidance is provided on when to use this tool versus alternatives like google_search, web_scrape, or other sibling search tools. The description lacks any mention of use cases, exclusions, or comparisons.

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