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TikTok MCP

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TikTok MCP

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The TikTok MCP integrates TikTok access into Claude AI and other apps via TikNeuron. This TikTok MCP allows you to

  • analyze TikTok videos to determine virality factors

  • get content from TikTok videos

  • chat with TikTok videos

Available Tools

tiktok_get_subtitle

Description:
Get the subtitle (content) for a TikTok video url. This is used for getting the subtitle, content or context for a TikTok video. If no language code is provided, the tool will return the subtitle of automatic speech recognition.

Input Parameters:

tiktok_get_post_details

Description:
Get the details of a TikTok post. Returns the details of the video like:

  • Description

  • Video ID

  • Creator username

  • Hashtags

  • Number of likes, shares, comments, views and bookmarks

  • Date of creation

  • Duration of the video

  • Available subtitles with language and source information

Input Parameters:

tiktok_search

Description:
Search for TikTok videos based on a query. Returns a list of videos matching the search criteria with their details including description, video ID, creator, hashtags, engagement metrics, date of creation, duration and available subtitles, plus pagination metadata for continuing the search.

Input Parameters:

  • query (required): Search query for TikTok videos, e.g., 'funny cats', 'dance', 'cooking tutorial'

  • cursor (optional): Pagination cursor for getting more results

  • search_uid (optional): Search session identifier for pagination

Related MCP server: tiktok-mcp

Install via MCPB (Easiest)

The easiest way to install the TikTok MCP in Claude Desktop is via the MCPB bundle — no cloning or building required.

  1. Download the latest tiktok-mcp.mcpb from the Releases page

  2. Open the .mcpb file — Claude Desktop will show an installation dialog

  3. Enter your TikNeuron API Key when prompted

That's it. Claude Desktop handles the rest automatically.

Requirements

For this TikTok MCP, you need

Setup

  1. Clone the repository

git clone https://github.com/Seym0n/tiktok-mcp.git

  1. Install dependencies

npm install

  1. Build project

npm run build

This creates the file build\index.js

Using in Claude AI

Add the following entry to mcpServers:

"tiktok-mcp": {
    "command": "node",
    "args": [
      "path\\build\\index.js"
    ],
    "env": {
      "TIKNEURON_MCP_API_KEY": "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
    }
}

and replace path with the path to TikTok MCP and XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX with TIkNeuron API Key

so that mcpServers will look like this:

{
  "mcpServers": {
    "tiktok-mcp": {
      "command": "node",
      "args": [
        "path\\build\\index.js"
      ],
      "env": {
        "TIKNEURON_MCP_API_KEY": "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
      }
    }
  }
}

Available Tools

3 tools
tiktok_get_post_detailsB

Get the details of a TikTok post.This is used for getting the details of a TikTok post.Supports TikTok video url (or video ID) as input.Returns the details of the video like - Description - Video ID - Creator username - Hashtags - Number of likes, shares, comments, views and bookmarks - Date of creation - Duration of the video - Available subtitles with language and source information

ParametersJSON Schema
NameRequiredDescriptionDefault
tiktok_urlYesTikTok video URL, e.g., https://www.tiktok.com/@username/video/1234567890 or https://vm.tiktok.com/1234567890, or just the video ID like 7409731702890827041

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It lists many return fields (likes, shares, comments, etc.), which is helpful, but does not disclose authentication, rate limits, or potential errors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately concise but has redundancy (first two sentences say similar things). It lists return fields in a bullet-like manner, which aids readability.

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

Completeness3/5

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

Given the tool has one parameter and no output schema, the description adequately covers input and output fields. However, it lacks context on error handling, authentication, or pagination if applicable.

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?

The schema already describes the parameter in detail, including URL formats and video ID example. The description adds minimal extra value; it mentions 'supports TikTok video url (or video ID)' which matches the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it gets post details and lists specific returned fields, distinguishing it from sibling tools like tiktok_get_subtitle and tiktok_search. However, the first two sentences are redundant.

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?

It implies use when post details are needed and specifies input formats (URL or video ID), but does not provide explicit when-to-use or when-not-to-use guidance compared to alternatives.

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

tiktok_get_subtitleA

Get the subtitle (content) for a TikTok video url.This is used for getting the subtitle, content or context for a TikTok video.Supports TikTok video url (or video ID) as input and optionally language code from the tool post detailsReturns the subtitle for the video in the requested language and format.If no language code is provided, the tool will return the subtitle of automatic speech recognition.

ParametersJSON Schema
NameRequiredDescriptionDefault
tiktok_urlYesTikTok video URL, e.g., https://www.tiktok.com/@username/video/1234567890 or https://vm.tiktok.com/1234567890, or just the video ID like 7409731702890827041
language_codeNoLanguage code for the subtitle, e.g., en for English, es for Spanish, fr for French, etc.

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the burden; it mentions automatic speech recognition fallback but omits other behaviors like rate limits, authorization, or error handling for missing subtitles.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description has some redundancy (e.g., 'Get the subtitle...' and 'This is used for getting...'). Could be more concise without losing clarity.

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

Completeness3/5

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

Adequate for a simple tool with two parameters, but lacks details on return format, error handling, and authentication requirements. Not thoroughly complete.

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 coverage is 100%, so parameters are already described. The description adds little beyond the schema, only mentioning the automatic speech recognition fallback for missing language code.

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 gets subtitles for TikTok videos using a URL or ID. This distinguishes it from siblings like tiktok_get_post_details and tiktok_search.

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 explains the tool is for getting subtitles and mentions optional language code. However, it does not explicitly state when not to use it or compare with alternatives.

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

A3.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: get post details, get subtitles, and search. No overlap, descriptions are clear and specific.

Naming Consistency5/5

All tools follow a consistent 'tiktok_verb_noun' pattern (get_post_details, get_subtitle, search). Naming is uniform and predictable.

Tool Count4/5

3 tools is appropriate for a focused TikTok MCP that provides core reading operations. Could be slightly expanded, but not under-scoped.

Completeness3/5

Covers search, post details, and subtitles, but missing user profiles, trending, or interaction features. Notable gaps for a comprehensive TikTok tool set.

Maintenance

ActivityMaintained
ResponsivenessSyncing

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