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thenavidm

ScrapeCreators MCP Server

by thenavidm

Comments

tiktok_comments

Fetch comments from a TikTok video URL to read audience reactions and replies. Returns comment text, likes, reply counts, and user details, with pagination via cursor.

Instructions

Fetches comments on a TikTok video by URL — useful for reading audience reactions, replies, and engagement. Returns comments, an array where each comment includes text, digg_count (likes), reply_comment_total, create_time, and a user object with the commenter's nickname and unique_id; also returns total comment count. Paginate with cursor from the previous response. Potentially consumes paid API credits; requires confirm=true. Read-like POST requests do not publish to social platforms.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesTikTok video URL
trimNoSet to true to get a trimmed response
cursorNoCursor to get more comments. Get 'cursor' from previous response.
accountNoNamed private ScrapeCreators account; selects credentials, not a remote account ID.
confirmNoMust be true for the specific approved credit-consuming research call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial behavioral context beyond annotations: it warns of paid credit consumption, mandates confirm=true, and clarifies that the read-like POST does not publish to social platforms — which resolves the apparent tension with readOnlyHint=false. This tells the agent about cost, safety, and side effects directly.

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?

Front-loaded with the core action, then return shape, then pagination and cost. The return-field enumeration is dense but justified given no output schema. Minor verbosity, but every element earns its place.

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?

With no output schema, the description compensates by documenting the returned `comments` array fields, `total`, and pagination. Combined with the credit/confirm safety notes, an agent has everything needed to invoke it correctly.

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 100% schema coverage the baseline is 3, but the description adds practical meaning by explaining that cursor pagination pulls from the previous response and that confirm is required for the credit-consuming call. It does not elaborate on account or trim, keeping it modest above baseline.

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 ('Fetches comments on a TikTok video by URL') and scopes it to a single video, which is distinguishable from siblings like tiktok_comment_replies and tiktok_video_info. An agent can tell what it retrieves without opening the schema.

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?

Frames the use case ('reading audience reactions, replies, and engagement') and explains pagination flows with 'cursor'. It does not explicitly route to a sibling (e.g., tiktok_comment_replies for replies) or state when not to use it, so it stops short of full routing guidance.

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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