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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 to include heavier payload fields in the response. Leave unset for the leanest response.

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and destructiveHint false, so safety profile is covered. The description adds behavioral context like country-specific searches, device emulation, and multi-page fetching, which are useful. However, it does not disclose response format, pagination behavior, or potential rate limits, leaving gaps beyond what annotations provide.

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-loading the core purpose and key capabilities. There is no fluff or repetition; every phrase adds value. It is appropriately sized for a tool with a well-covered schema.

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

Completeness2/5

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

Given a complex 7-parameter tool with a nested include object and no output schema, this description is incomplete. It does not explain the return structure, pagination semantics, or the purpose of the include flags. An agent would need to infer response details, which is a significant gap for a scraping tool.

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 all parameters have documented meaning. The description does not add any parameter-specific details beyond what the schema already provides; it only loosely implies country and pages via phrasing. Baseline 3 is appropriate as the schema carries full parameter documentation.

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 runs a Google News search and returns news results, with support for device emulation and multi-page results. It distinguishes itself from siblings by naming the Google News resource explicitly, though it does not directly reference an alternative like scrape_google. The purpose is unambiguous given the tool name.

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?

The description provides no guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. There is no reference to siblings or conditions like 'use this for news-specific queries vs. general web search', leaving the agent without routing context.

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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TDQS

A4/5.0
Disambiguation5/5

Each tool targets a distinct engine or product (ChatGPT, Copilot, Gemini, Google, Google News, etc.), and the descriptions clearly specify what each scrape returns. The only potential overlap is between Google search and Google AI Mode, but the descriptions separate them effectively.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern: list_* for metadata and scrape_* for retrieval operations. The engine-specific names like scrape_chatgpt and scrape_google_ai_mode are predictable and easy to group.

Tool Count5/5

Ten tools is a well-scoped size for a geo-targeted search and AI answer scraping server. Each tool covers a meaningful engine or metadata requirement without excessive redundancy.

Completeness4/5

The tool surface covers major AI assistants, Google search variants, news, and supporting geo-targeting metadata. Minor gaps exist such as no standalone Bing/DuckDuckGo scraper or explicit engine model listing, but the core workflows are well supported.

Resources