Skip to main content
Glama

Social Media Search API — Twitter, Instagram, Reddit, TikTok (XPOZ)

getTiktokCommentsByPostId

Read-only

Get COMMENT CONTENT (text, likes) for a Tiktok post. Returns the actual comment objects with text and metadata. RETURNS COMMENT DATA: id, text, username, createdAtDate, likeCount. Use for reading what people said. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Auto API fallback for fresh data. PAGING (responseType="paging"): Async paginated results (100/page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. CSV (responseType="csv"): Async single CSV download, returns operationId, poll for S3 link. CODE EXECUTION: For csv mode, download CSV and use code execution to analyze full dataset. Ideal for: sentiment analysis, reading discussions, analyzing comment content, engagement patterns. Date filters: OMIT startDate/endDate by default. ONLY pass if user explicitly requests date range. IMPORTANT!!!!!: THE CURRENT YEAR IS 2026. When user requests relative dates (last week, last month), verify the current date from your system context and double-check the calculated dates - models often get the year wrong, searching one year earlier than intended. Optional fields: ["id", "text", "username", "createdAtDate", "likeCount"]. This is a safe, read-only tool for analyzing searchable information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return. Fast mode: capped at 300 (default: 300). Paging/CSV modes: caps total exported rows (default: all, max 500K).
fieldsNoPERFORMANCE OPTIMIZATION: Specify fields you need. DEFAULT (if omitted): ["id", "text", "username", "createdAtDate"]. AVAILABLE FIELDS: Core: id, text, postId, userId, username, createdAt, createdAtTimestamp, createdAtDate. Engagement: likeCount. EXAMPLES: ["id", "text"] for minimal, ["id", "text", "username", "createdAtDate", "likeCount"] for basic analysis.
postIdYesTiktok post ID to fetch comments for.
endDateNo
_isTrialNo
feedbackNoOptional. Any free-form feedback you want to share — about this tool, other tools, the platform overall, or anything else. Feedback does NOT have to be about the current tool: you can use this field to comment on a different tool you used earlier, flag missing functionality, request a new tool, or share general impressions. Examples: "wish getTwitterPostsByKeywords supported language filtering", "auth flow was confusing", "would be useful to have a tool that lists the members of a Twitter list", "loved how fast this was". Captured for product feedback; does not affect tool behavior.
startDateNo
tableNameNoCached table name from previous pagination request. Required when fetching pageNumber > 1. Returned in first page response.
_requestIdNo
pageNumberNoPage number to fetch (1-indexed). Must be provided with tableName to fetch subsequent pages. Omit for first page.
userPromptNoCRITICAL FOR ACCURACY: Include the complete user question to enable query optimization and context-aware filtering.
_trialTokenNo
forceLatestNoUSE SPARINGLY: Force fetching the latest data from the API, bypassing cache checks. Only use when explicitly required (e.g., "get the latest", "most recent", "real-time"). WARNING: Increases latency and API costs. Default: false (uses intelligent caching).
responseTypeNoResponse mode. "fast" (default): returns up to 300 results directly (use limit param to reduce). "paging": async paginated results (100/page), poll via checkOperationStatus. "csv": async single CSV download, poll for S3 link.
pageNumberEndNoOptional ending page number for fetching multiple consecutive pages at once. Must be >= pageNumber. Requires tableName.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / feedback / description
      Previous value: -"Optional. Any free-form feedback you want to share — about this tool, other tools, the platform overall, or anything else. Feedback does NOT have to be about the current tool: you can use this field to comment on a different tool you used earlier, flag missing functionality, request a new tool, or share general impressions. Examples: \"wish getTwitterPostsByKeywords supported language filtering\", \"auth flow was confusing\", \"would be useful to have a getTwitterListMembers tool\", \"loved how fast this was\". Captured for product feedback; does not affect tool behavior."New value: +"Optional. Any free-form feedback you want to share — about this tool, other tools, the platform overall, or anything else. Feedback does NOT have to be about the current tool: you can use this field to comment on a different tool you used earlier, flag missing functionality, request a new tool, or share general impressions. Examples: \"wish getTwitterPostsByKeywords supported language filtering\", \"auth flow was confusing\", \"would be useful to have a tool that lists the members of a Twitter list\", \"loved how fast this was\". Captured for product feedback; does not affect tool behavior."
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds substantial behavioral context: response modes (fast, paging, csv), pagination mechanics with operationId polling, CSV download flow, auto API fallback, caching behavior with forceLatest, and a warning about year miscalculation. This goes well beyond the annotations and fully discloses operational nuances.

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 long but meticulously organized into sections (FAST, PAGING, CSV, CODE EXECUTION, date filters) with clear headers. It front-loads the core purpose and returns data, then provides mode-specific details. Each sentence serves a purpose, including the current-year warning which prevents common errors. No redundant filler.

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?

Given the tool's complexity (15 parameters, multiple response modes, no output schema), the description is exceptionally complete. It covers return fields, all response modes, pagination and CSV workflows, caching, performance, and date handling. It also explains how to analyze CSV data via code execution. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 67% schema coverage, the description enriches almost every parameter. It explains limit caps per mode, provides field examples and performance optimization, details responseType modes, warns about forceLatest latency/cost, explains pageNumber/tableName for pagination, and clarifies date filter defaults. This compensates for any schema gaps and adds meaningful semantics beyond the raw property descriptions.

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 clearly states the tool retrieves comment content (text, likes) for a TikTok post, returning specific fields (id, text, username, createdAtDate, likeCount). It is unambiguous and distinct from sibling tools like getTwitterPostComments or getInstagramCommentsByPostId due to the platform-specific naming and content focus.

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?

The description provides explicit when-to-use guidance: 'Use for reading what people said' and lists ideal use cases like sentiment analysis and engagement patterns. It also gives clear directives on date filters ('OMIT startDate/endDate by default. ONLY pass if user explicitly requests date range'). However, it does not name alternative tools for different platforms or contexts, so it stops short of explicit exclusions relative to siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.