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CreatorDB

creatordb-mcp-server

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by CreatorDB

search_tiktok_content

Search TikTok videos by content filters such as description, hashtag, plays, likes, comments, shares, and engagement. Retrieve individual post details including metrics and creator info.

Instructions

Search individual TikTok content (videos) across CreatorDB's index. Different from search_tiktok (which searches CREATORS) — this returns individual posts. Response includes contentList[] with contentId, description, thumbnail, url, publishTime (Unix-ms), lengthSec, plays/likes/comments/shares/engagementRate, hashtags, audioTitle, audioAuthor, and a nested creator block. NO contentType field. NO isSponsored / partneredBrands — TikTok brand-attribution is not implemented (native isAd flag exists on get_tiktok_content_detail only). Content-level filterable: description, hashtag, publishTime (integer "days ago"), plays, diggs (request name) / likes (response name), comments, shares, engagement, lengthSec, performanceDiggs, performanceEngagement. Creator-level filters also supported. Engagement formula = (likes+comments+shares)/followers. Costs 2 credits per page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersYesContent filters (1–10).
pageSizeNoResults per page (max 100).
offsetNoNumber of records to skip for pagination.
sortByNoSort field.publishTime
descNoSort descending (true) or ascending (false).
Behavior4/5

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

Discloses response structure, missing fields (no contentType, no isSponsored), engagement formula, and brand-attribution limitations. Adds context beyond typical, though no annotations are present to rely on.

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 single paragraph with front-loaded purpose; all sentences add value. Could benefit from bullet points but length is justified by complexity.

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?

Covers essential aspects: what it returns, what it doesn't, filterable fields, sorting, cost. Lacks explicit pagination explanation but offset/pageSize are in schema.

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?

Adds value beyond 100% schema coverage by listing filterable fields in natural language, clarifying request/response naming (diggs vs likes), and explaining engagement formula.

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?

Clearly states it searches individual TikTok videos, distinguishes from sibling search_tiktok (creators), and specifies the resource as 'individual posts'.

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?

Explicitly contrasts with search_tiktok for creators, lists filterable fields, notes cost per page. Could add explicit when-not-to-use scenarios but is sufficient.

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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