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Show Ad Carousel

show_ad_carousel
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Render a visual ad carousel widget inline (resource: ui://carousel-mcp-v4). Use this AFTER get_meta_ads, search_meta_ads_by_keyword, get_google_ad_details, search_linkedin_ads, or search_tiktok_ads to show selected ads. Works across ALL FOUR platforms (Meta, Google, LinkedIn, TikTok) and you may mix them in one carousel. Model leads in text — call this when the user benefits from visual evidence of the ads referenced. Call it multiple times in one response, once per point you make — not one carousel for all ads. Pass only the ads that evidence one point: a single creative for one claim, a handful for a pattern. The carousel UI holds 20 ads max — a hard safety cap, not a target; split overflow across another call. Per ad, pass ONLY the identifier ref copied from the prior tool's text output: Meta ads as {ad_id, page_id} (ad_id required, page_id recommended); Google ads as {ad_url}; LinkedIn ads as {linkedin_id}; TikTok ads as {tiktok_id}. Google ads MUST have gone through get_google_ad_details first (it warms the creative cache) — otherwise this call spends credits refetching. LinkedIn ads are warmed by search_linkedin_ads; an uncached one is refetched by id. TikTok ads are warmed by search_tiktok_ads; a stale ref is refetched by tiktok_id (1 credit). Do NOT copy body, headline, media_url, cards or any other field: the server reconstructs the full ad from its own cache, so anything else you pass is discarded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adsYesUp to 20 ad refs copied from earlier tool output: Meta {ad_id, page_id}, Google {ad_url}, LinkedIn {linkedin_id}, TikTok {tiktok_id}. Other fields are ignored.
contextNoOne plain sentence, 8-20 words, starting with a verb, stating what the user is trying to accomplish in this conversation. Name the brand, competitor, industry, or topic involved. Reuse the exact same sentence on every tool call in this conversation. Never include people's names, emails, phone numbers, credentials, or internal company details. Never describe this tool or why it was chosen. Example: 'Compare Notion and Coda Meta ads to find hooks for a productivity app launch.'
conversation_idNoEcho the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_mcp_instructionsNoServer-issued metadata for this conversation.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / ads / description
      Added value: +"Up to 20 ad refs copied from earlier tool output: Meta {ad_id, page_id}, Google {ad_url}, LinkedIn {linkedin_id}, TikTok {tiktok_id}. Other fields are ignored."
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the annotations: discloses a hard 20-ad cap, cache-warming prerequisites for Google/LinkedIn/TikTok with credit-spend consequences for refetching, and that non-identifier fields are discarded because the server reconstructs from its own cache. Annotations cover only read-only safety.

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?

Dense and front-loaded with the action and the upstream dependency, but it is long and duplicates the context/conversation_id guidance already present in the schema, which dilutes an otherwise efficient definition.

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 an output schema exists, return values need not be explained. The description nevertheless covers caching, credit costs, the safe cap, overflow handling, and per-platform ref formats, leaving no material gap for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: per-platform ref shapes with required vs recommended fields (ad_id required, page_id recommended) and the strong constraint that body/headline/media_url/cards are ignored. It largely restates the context/conversation_id rules already in the schema.

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?

States a specific verb and resource ('Render a visual ad carousel widget inline') plus the resource URI, and makes clear this is a display step rather than a fetch step, distinguishing it from get_meta_ads/search_* siblings.

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

Usage Guidelines5/5

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

Explicitly names the upstream tools to call first (get_meta_ads, search_meta_ads_by_keyword, get_google_ad_details, etc.) and the condition that selects this tool ('when the user benefits from visual evidence'). It also prescribes invocation cadence ('call multiple times, once per point') and scoping ('pass only the ads that evidence one point').

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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