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Scrape Google News

scrape_google_news
Read-only

Run a Google News search from a chosen country and return news results. Supports desktop, mobile, iOS, and Android emulation and multi-page results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glNoISO 3166-1 alpha-2 code for the result geography, sent to Google as gl (e.g. "us"). Use list_countries to see supported codes per model.
hlNoOptional Google interface-language code, sent as hl (e.g. "de", "pt-br"). Defaults to the language derived from gl — set it when the geography's dominant language is not the one you want.
pagesNoNumber of result pages to fetch (1-10). Defaults to 1.
queryYesThe search query.
deviceNoDevice to emulate: desktop, mobile, ios (Safari on iPhone), or android (Chrome on Android). mobile is an alias for android. Defaults to desktop.desktop
countryNoISO 3166-1 alpha-2 country code to geo-target the request from (e.g. "US"). Use list_countries to see supported codes per model. Deprecated — use gl instead; country is kept for compatibility and must not disagree with gl.
includeNoOptional flags for heavier payload fields, each off by default: markdown (the answer rendered as markdown), html (the answer page HTML), rawResponse (the engine's unprocessed response payload). Leave unset for the leanest response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / include / description
      Previous value: -"Optional flags to include heavier payload fields in the response. Leave unset for the leanest response."New value: +"Optional flags for heavier payload fields, each off by default: markdown (the answer rendered as markdown), html (the answer page HTML), rawResponse (the engine's unprocessed response payload). Leave unset for the leanest response."
  2. Changed4 schema fields changed
    • changedInput schema / properties / country / description
      Previous value: -"ISO 3166-1 alpha-2 country code to geo-target the request from (e.g. \"US\"). Use list_countries to see supported codes per model."New value: +"ISO 3166-1 alpha-2 country code to geo-target the request from (e.g. \"US\"). Use list_countries to see supported codes per model. Deprecated — use gl instead; country is kept for compatibility and must not disagree with gl."
    • addedInput schema / properties / gl
      Added value: +{
+  "description": "ISO 3166-1 alpha-2 code for the result geography, sent to Google as gl (e.g. \"us\"). Use list_countries to see supported codes per model.",
+  "type": "string"
+}
    • addedInput schema / properties / hl
      Added value: +{
+  "description": "Optional Google interface-language code, sent as hl (e.g. \"de\", \"pt-br\"). Defaults to the language derived from gl — set it when the geography's dominant language is not the one you want.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "query",
-  "country"
-]New value: +[
+  "query"
+]
  3. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already mark the operation as read-only and non-destructive, so the safety burden is covered. The description adds meaningful behavioral context by disclosing device emulation (desktop/mobile/iOS/Android) and multi-page result fetching, which an agent cannot infer from the annotations.

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?

Two tight sentences with no filler: the core action leads, followed by the two most relevant capability expansions (device emulation, pagination). Every sentence adds 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?

With seven parameters, a nested include object, and no output schema, the description should tell an agent what a response looks like; 'return news results' is vague. The schema covers parameters and annotations cover safety, so the main remaining gap is the unspecified result shape and any pagination/rate-limit caveats.

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 the schema already documents all seven parameters thoroughly, making the baseline 3. The tool description itself adds little parameter meaning beyond 'chosen country', but it doesn't need to because the schema carries the burden.

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 names a specific verb ('Run a Google News search'), a concrete resource, and the result type ('return news results'), which clearly distinguishes it from siblings like scrape_google and scrape_google_ai_mode. It also adds useful scope ('from a chosen country') and capabilities.

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 this is the tool to use for Google News searches, but it never explicitly contrasts it with the sibling scrape_google or states when not to use it. There is no mention of alternatives or exclusion criteria, so the usage guidance is only inferred from the tool's purpose.

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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