Skip to main content
Glama

captapi

by io.github.CDCStream

google_ad_library_ad_details

Google publishes spend and impression ranges only for election ads; commercial advertisers omit both. isActive is true when lastShown is within 7 UTC days. Costs 2 credits. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cacheNoSet true to serve from the 24h response cache (0 credits on hit). Default false — always fetch fresh.
countryNoTwo-letter ISO country code. Default US.
creative_idYesGoogle Ads Transparency URL containing AR... advertiser and CR... creative IDs.

TDQS

B3.1/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden, and it discloses several non-obvious traits: crediting cost, no charge on empty/failed results, 24h cache behavior, the definition of isActive, and that spend/impression ranges only appear for election ads. It stops short of covering auth or rate limits, but it is notably transparent for practical invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and information-dense: four short sentences cover data availability, field semantics, billing, and caching. It is well-structured and front-loaded with a key caveat, though it would be slightly clearer if the core purpose statement came first.

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?

The description covers operational details well—credits, caching, failure charges, and one field definition—and the schema covers all parameters. However, with no output schema and no explicit statement of what 'ad details' includes or how this tool differs from google_ad_library_company_ads, an agent is left to infer the tool's main return content and selection context.

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 baseline is 3. The description essentially restates the cache parameter behavior that already appears in the schema and adds nothing new about creative_id or country. It does not compensate with extra semantic detail beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description never explicitly states that this tool fetches details for a single Google Ad Library ad; it jumps straight into caveats about spend/impression availability, isActive semantics, credits, and caching. The tool name and the required creative_id make the purpose inferable, but the description itself lacks a clear verb+resource statement.

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?

There is no guidance on when to use this tool versus sibling tools like google_ad_library_company_ads or google_ad_library_advertiser_search. The only usage advice is about passing cache=true for a free cache hit, which is parameter-level, not tool-selection guidance.

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

All captapi toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.2/5.0
Disambiguation3/5

The platform-prefix convention keeps most of the 178 tools clearly separated, but several clusters are genuinely ambiguous: tiktok_live_info is explicitly described as 'Identical to TikTok Live', instagram_basic_profile and instagram_channel_details both return profile stats, and facebook_profile_posts overlaps with facebook_profile_reels. The generic 'Summarizer' descriptions for facebook_summarize, instagram_summarize, and tiktok_summarize provide no disambiguating detail at all.

Naming Consistency4/5

The dominant snake_case platform_resource_suffix pattern is followed remarkably consistently across 178 tools (e.g. youtube_channel_videos, tiktok_search_users, reddit_subreddit_posts). Minor deviations exist: the same creator resource is called 'channel' in some tools (tiktok_channel_details, instagram_channel_posts) but 'profile' or 'user' in others (facebook_profile_posts, twitch_user_videos, linnkme_profile); link-in-bio tools mostly use _page but linkme uses _profile; and the video_summarize/video_transcript pair lacks a platform prefix.

Tool Count2/5

At 178 tools this is far beyond what any agent can efficiently navigate in a single flat namespace, and even individual platform subsets exceed reasonable bounds (TikTok alone has ~34 tools, YouTube ~25). The sheer breadth of the multi-platform scope partially justifies the count, but the server would be far more usable split into per-platform servers.

Completeness4/5

The read-only data surface is impressively thorough: nearly every platform has profile + content + search + comments coverage, and TikTok, YouTube, Instagram, and Facebook are covered end-to-end including shops, ads, transcripts, and summaries. Notable gaps are minor: Twitter has no keyword search tool, LinkedIn lacks comments, and Reddit has no user-profile endpoint, but none of these create dead ends for the server's core data-retrieval purpose.

Resources