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Search TikTok Ads

search_tiktok_ads
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Search TikTok's public ads library (EU DSA) by advertiser name. Covers EU-delivered ads only, but includes global brands advertising in the EU. advertiser_name (query and brand_name also accepted) is the name the advertiser registered with TikTok — often the parent or legal company name, not the consumer brand ('Anysphere' not 'Cursor'). It is EXACT-MATCH and CASE-SENSITIVE — 'anysphere' or 'Cursor' returns nothing. On zero results, retry with different capitalization, the parent/legal company name, or find it via library.tiktok.com. Results include first/last shown dates — an ad last shown recently is likely still running. No engagement metrics at search level; use get_tiktok_ad_details for landing page and targeting. SHOWING THE ADS — you MUST call show_ad_carousel at least once this turn so the user SEES the TikTok creatives as visual proof, not only reads about them. Pass each TikTok ad as {tiktok_id} copied from this tool's output (the server fills creative, cover and body from cache). Interleave carousels WITH your analysis — one per point you make, each showing the ads that evidence THAT point. Structure strictly as point → its carousel → next point → its carousel; NEVER stack carousels back-to-back or dump all points as a list after the carousels. Be generous: across your carousels, show MOST of the ads this tool returned (up to 20 per carousel) — skip only irrelevant or near-duplicate ads; never render just 2-3 when a dozen were found. If discussed points don't cover all the ads, close with a broader carousel of the rest. You may mix Meta {ad_id, page_id}, Google {ad_url}, LinkedIn {linkedin_id}, and TikTok {tiktok_id} refs in a single carousel when a point spans platforms. Skip it only when there were zero ads.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoAlias for advertiser_name.
cursorNoOpaque pagination token from a previous response.
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.'
brand_nameNoAlias for advertiser_name.
advertiser_nameNoName the advertiser registered with TikTok, often the parent or legal company rather than the consumer brand ("Anysphere" not "Cursor"). Exact-match and case-sensitive.
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. Changed4 schema fields changed
    • addedInput schema / properties / advertiser_name / description
      Added value: +"Name the advertiser registered with TikTok, often the parent or legal company rather than the consumer brand (\"Anysphere\" not \"Cursor\"). Exact-match and case-sensitive."
    • addedInput schema / properties / brand_name / description
      Added value: +"Alias for advertiser_name."
    • addedInput schema / properties / cursor / description
      Added value: +"Opaque pagination token from a previous response."
    • addedInput schema / properties / query / description
      Added value: +"Alias for advertiser_name."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false. The description adds valuable behavioral context beyond annotations: exact-match and case-sensitive matching semantics, EU-only coverage, that results include first/last shown dates, that no engagement metrics exist at search level. It does not cover rate limits or pagination behavior, keeping it from a 5.

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

Conciseness3/5

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

The first half is tight and front-loaded with the search contract. The second half ('SHOWING THE ADS') is a long procedural block about carousel sequencing that belongs to show_ad_carousel's contract, not this tool's search contract; it bloats this tool's description significantly. It earns some place because it's a cross-tool requirement, but the volume is disproportionate.

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

Completeness4/5

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

An output schema exists, so return values need not be explained, and the description correctly focuses on the search contract. It covers scoping, matching semantics, and result fields. The main gap is pagination (cursor exists but isn't explained beyond the schema description) and no rate-limit context. Adequate for the complexity, though the carousel digression dilutes focus.

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 schema already documents all six parameters including the aliases. The description nonetheless adds real semantic value: it explains that query and brand_name are aliases for advertiser_name, that the match is exact/case-sensitive, and gives the crucial hint that the value is often the parent/legal name (Anysphere vs Cursor). That's meaning beyond the schema, so a 4.

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+resource+scope: search TikTok's public EU DSA ads library by advertiser name. It also distinguishes itself from the sibling get_tiktok_ad_details by naming the boundary (search-level vs details). An agent can tell this apart from search_meta_ads_by_keyword and get_tiktok_ad_details immediately.

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?

Explicit when-to-use and when-not-to-use: it says to retry with different capitalization on zero results, to point to library.tiktok.com as fallback, to use get_tiktok_ad_details for landing page/targeting, and to ONLY call show_ad_carousel when ads exist. This is unusually explicit routing.

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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