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rugvedp

All About Ads MCP

search_google

Read-only

Search Google for organic results to research brands, news, and ad context with customizable queries, pagination, country, language, and date filters.

Instructions

Search Google for organic results to research brands, news, and ad context.

Runs a remote scraper (30s–few minutes). Full results are saved to a JSON file; only a compact preview is returned inline. Use read_saved_results to page through the full dataset without flooding context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYesSearch queries to run, e.g. ['nike ad strategy 2025', 'adidas campaign news'].
country_codeNo2-letter country code controlling the Google domain, e.g. 'gb' → google.co.uk. None uses google.com.
search_languageNoLanguage code to filter results by, e.g. 'en', 'fr', 'de'.
quick_date_rangeNoRelative date filter: d<N> (days), w<N> (weeks), m<N> (months), y<N> (years). E.g. 'd10', 'w2', 'm6'.
results_per_pageNoResults per page, between 10 and 100.
max_pages_per_queryNoNumber of result pages per query. Each page contains ~10 results.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queriesYes
resultsYes
file_pathYes
result_countYes
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds valuable behavioral context: it runs a remote scraper (30s–few minutes), saves full results to a JSON file, returns only a compact preview, and refers to read_saved_results for paging. No contradictions.

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 three sentences, front-loading the purpose, then adding behavioral details. Every sentence is informative with no fluff.

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

Completeness5/5

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

Given the tool's moderate complexity (remote scraper, multiple parameters, result storage), the description explains the asynchronous behavior, result handling, and how to access full results. The presence of an output schema covers return values, making this description complete for an agent.

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 coverage is 100%, with each parameter described. The description does not add further meaning beyond what the schema provides for parameters. Baseline score of 3 is appropriate.

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 searches Google for organic results, specifying the verb 'search', the resource 'Google for organic results', and the research purpose ('brands, news, and ad context'). It distinguishes from sibling tools like search_google_ads and search_facebook_ads.

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

Usage Guidelines4/5

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

The description provides clear context on when to use this tool vs. read_saved_results, explaining that full results are saved and only a compact preview is returned. However, it does not explicitly mention when not to use this tool or provide alternatives among other search siblings.

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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