API Direct

search_tiktok

Search TikTok videos by keyword.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`pages`	No	Number of pages to fetch, 1-10 (default: 1)
`query`	Yes	Search keyword (max 500 characters)
`region`	No	2-letter region code, e.g. "us", "gb", "jp"
`sort_by`	No	Sort order: "relevance", "most_recent", or "most_liked"	relevance
`publish_time`	No	Time filter: 0=ALL, 1=24h, 7=week, 30=month, 90=3months, 180=6months
`get_sentiment`	No	Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small per-page surcharge.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedAug 17, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the core action and does not mention pagination, sorting, region filtering, or the sentiment analysis surcharge, all of which are relevant behavioral traits.

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 a single sentence with no filler or redundant phrasing, making it concise and front-loaded with the essential purpose.

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

Completeness2/5

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

Despite the schema covering parameters, the description provides no information about return format, pagination limits, or the sentiment surcharge. With no output schema and moderate complexity, the description is not complete enough for full agent understanding.

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 adds little beyond the schema, only implicitly mapping 'keyword' to the query parameter, but it does not clarify any additional parameter semantics.

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 uses a specific verb 'search' with a clear resource 'TikTok videos' and qualifier 'by keyword', making it obvious what the tool does and distinguishing it from sibling tools like search_tiktok_users and tiktok_video_details.

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

Usage Guidelines3/5

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

The description implies usage for keyword-based TikTok video search but provides no explicit when-to-use or alternative guidance. It does not mention alternatives like search_instagram or search_twitter for other platforms, leaving the agent to infer context from the tool name.

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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TDQS

B3.1/5.0

Disambiguation4/5

Most tools are clearly scoped by platform and resource (e.g. search_twitter vs twitter_user_tweets vs twitter_tweet_details). A few pairs like twitter_tweet_comments vs twitter_user_replies or facebook_page_posts vs search_facebook_posts could cause minor confusion, but descriptions generally clarify the distinction.

Naming Consistency4/5

The dominant pattern is snake_case with a platform_prefix_resource suffix, and search_* consistently marks search operations. Minor deviations include noun-style names like amazon_best_sellers and place_photos, and the odd get_ skill/comments tools, but the overall convention is predictable.

Tool Count2/5

74 tools is far beyond the typical well-scoped MCP server, even for a multi-platform API aggregator. The breadth is justified by the many platforms covered, but an agent will face a very large action space, and this could reasonably be split into per-platform servers.

Completeness4/5

The server provides strong lifecycle coverage for its read-only domain: search, profile/details, posts, and engagement data across most platforms. Gaps exist for some platforms (e.g. no LinkedIn person profile, no Facebook event details, no Truth Social profile/search, no Reddit subreddit-specific tools), but the core workflows are well covered.

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