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Influship Influencer Marketing MCP

Get YouTube channel transcripts

get_youtube_channel_transcripts
Read-only

Fetch transcripts for a selected batch of videos from a YouTube channel.

Choose the video count, ordering, language, and whether timestamped segments are included. This is a metered batch request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelYesA handle, channel ID, or YouTube channel URL.
sort_byNonewest
languageNoen
video_limitNo
include_segmentsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
dataNo
countNo
resultsNo
has_moreNo
not_foundNo
next_cursorNo
suggested_followupsNo

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context beyond those annotations, notably that the request is metered/cost-sensitive and that output granularity depends on include_segments and video_count, making the tool's behavior more predictable.

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 tightly structured: the first sentence states the action and resource, the second lists the primary configurable dimensions, and the final warning ('metered batch request') is useful caution with no fluff. Every sentence earns its place.

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?

The description is adequate for a read-only batch tool with an output schema and clear annotations, covering the key decision dimensions and metering behavior. What is missing is an explicit pointer to the single-video transcript sibling tool for non-batch needs, though 'batch' in the name and description make this reasonably inferable.

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?

With only 20% schema description coverage, the description carries the burden for the other parameters. It maps 'video count,' 'ordering,' 'language,' and 'timestamped segments' respectively to video_limit, sort_by, language, and include_segments. It does not restate concrete values, but those are already captured by enum/default/constraint 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?

The description states a specific verb ('Fetch'), a clear resource (YouTube channel transcripts), and narrows the scope to a 'selected batch of videos,' which distinguishes it from single-video transcript tools like get_youtube_video_transcript and channel metadata tools like get_youtube_channel.

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 batch usage with 'selected batch' and notes it is a 'metered batch request,' but it does not explicitly mention alternatives or when-not-to-use conditions. An agent can infer the intended use case from the batch wording, but the routing is not made explicit.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping boundaries: autocomplete_creators and search_creators are described as near-equivalent fuzzy lookups, get_creator and get_profile both resolve exact platform+username input, and the Instagram/TikTok post helpers overlap with generic get_posts. The descriptions work hard to disambiguate, but an agent would frequently need to choose between two or three equally plausible tools.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern, such as get_youtube_video, search_creators, match_creators, and render_creator_profile. Minor inconsistencies exist: singular/plural variants (get_instagram_post vs get_instagram_posts), list_ vs get_ for video listing, and search_creators carrying legacy semantic behavior under a lookup-sounding name.

Tool Count2/5

Twenty-eight tools places the server in the 'too many' range, and the count is inflated by near-duplicates like autocomplete_creators/search_creators, get_creator/get_profile, and singular/batch transcript variants. Even with three social platforms and rendering helpers, the surface would be more focused around 18–22 tools.

Completeness4/5

The core influencer research workflow is well covered: handle resolution, batch lookup, semantic discovery, lookalikes, posts, transcripts, YouTube search, matching, and comparison rendering. Gaps are minor—there is no creator shortlist persistence or cross-platform comment support—but the main discovery-to-match path has no dead ends.

Resources