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TikTok MCP Server

TikTok MCP Server

A hosted Model Context Protocol (MCP) server that gives Claude, Cursor, Windsurf and any other MCP client four read-only TikTok tools. Look up a public profile, walk an account's videos, read the comments on a video, and search TikTok for videos or creators, all as structured JSON, with no TikTok developer account and no OAuth.

It reads public data that a signed-out visitor can see. It does not sign in, post, or act as an account.

1,000 free credits every month, no card required, which is 100 TikTok calls.

https://mcp.hasdata.com/api/mcp?apis=tiktok

Glama score tool contract MCP Tools npm PyPI License

Contents

Related MCP server: tiktok-mcp

What you need

An MCP client and a HasData API key from the dashboard, free to create. This is a remote server, so the simplest path is a URL and an x-api-key header, with no container to run and no TikTok developer account anywhere in the flow. A client that only speaks stdio reaches it through a thin launcher, published as @hasdata/tiktok-mcp on npm and hasdata-tiktok-mcp on PyPI, shown below.

Quick start

The server URL is the same for every client. We run it hands-on in Claude Code and Claude Desktop. The other blocks follow each client's own documented format for a remote server.

Field

Value

URL

https://mcp.hasdata.com/api/mcp?apis=tiktok

Transport

HTTP, streamable

Auth header

x-api-key: HASDATA_API_KEY

Clients with OAuth support can add the same URL as a connector and sign in without putting a key in a config file.

claude mcp add --transport http tiktok "https://mcp.hasdata.com/api/mcp?apis=tiktok" \
  --header "x-api-key: HASDATA_API_KEY"

Settings, then Connectors, then Add custom connector, then paste https://mcp.hasdata.com/api/mcp?apis=tiktok and sign in.

For the config-file route, Claude Desktop loads only local (stdio) servers, so it reaches a remote server through a stdio launcher. The @hasdata/tiktok-mcp package is that launcher, and it reads the key from the environment. Add this to claude_desktop_config.json:

{
  "mcpServers": {
    "tiktok": {
      "command": "npx",
      "args": ["-y", "@hasdata/tiktok-mcp"],
      "env": { "HASDATA_API_KEY": "YOUR_KEY" }
    }
  }
}

Python instead of Node? Swap the launcher for the PyPI package, which uvx runs without a manual install:

{
  "mcpServers": {
    "tiktok": {
      "command": "uvx",
      "args": ["hasdata-tiktok-mcp"],
      "env": { "HASDATA_API_KEY": "YOUR_KEY" }
    }
  }
}

~/.cursor/mcp.json for every project, or .cursor/mcp.json for one:

{
  "mcpServers": {
    "tiktok": {
      "url": "https://mcp.hasdata.com/api/mcp?apis=tiktok",
      "headers": { "x-api-key": "HASDATA_API_KEY" }
    }
  }
}

~/.codeium/windsurf/mcp_config.json. Windsurf calls the field serverUrl, not url:

{
  "mcpServers": {
    "tiktok": {
      "serverUrl": "https://mcp.hasdata.com/api/mcp?apis=tiktok",
      "headers": { "x-api-key": "HASDATA_API_KEY" }
    }
  }
}
{
  "mcpServers": {
    "tiktok": {
      "url": "https://mcp.hasdata.com/api/mcp?apis=tiktok",
      "type": "streamableHttp",
      "headers": { "x-api-key": "HASDATA_API_KEY" },
      "disabled": false
    }
  }
}

.vscode/mcp.json in the workspace:

{
  "servers": {
    "tiktok": {
      "type": "http",
      "url": "https://mcp.hasdata.com/api/mcp?apis=tiktok",
      "headers": { "x-api-key": "HASDATA_API_KEY" }
    }
  }
}

~/.codex/config.toml:

[mcp_servers.tiktok]
url = "https://mcp.hasdata.com/api/mcp?apis=tiktok"

[mcp_servers.tiktok.headers]
"x-api-key" = "HASDATA_API_KEY"

~/.gemini/settings.json:

{
  "mcpServers": {
    "tiktok": {
      "httpUrl": "https://mcp.hasdata.com/api/mcp?apis=tiktok",
      "headers": { "x-api-key": "HASDATA_API_KEY" }
    }
  }
}

Example prompts

Prompts, not code. Paste one in and the agent picks the tool itself. Each is annotated with the calls it takes, because in MCP the model decides how many calls to make and every successful call costs 10 credits.

Take @mrbeast. Pull the profile, then walk the first two pages of videos and give me the median play count across them.

Three calls, 30 credits. The profile is one call, and each page of videos is another.

Search TikTok for creators around "cold brew coffee" and rank the top ten by followers, each with their bio.

One call, 10 credits. A user search already carries follower count and bio, so no per-profile follow-up is needed.

Here is a video URL. Read its top comments and tell me the overall sentiment and the three most-liked replies.

One call, 10 credits. The numeric id in the URL is all the comments tool needs.

Take that same video, then expand the replies under its most-liked comment.

Two calls, 20 credits. Top-level comments first, then a second call with that comment's id for its replies.

Search "asmr" videos, then pull the author profile of the three with the highest play counts.

Four calls, 40 credits. One search, then one profile each. Every author in a search result carries a link straight to its profile endpoint, so the agent never has to guess a handle.

Paging costs a call each time. A creator audit that reads a profile then walks five pages of videos is six calls and 60 credits. The free tier goes further on narrow questions than on open-ended crawls.

Tools

Four tools, all read-only. Samples below are trimmed from real calls, and the numbers in them move as TikTok updates. Read them as shapes. Each tool name links to its endpoint reference, which carries the full field list.

The samples are the payload, not the whole response. A tools/call result carries one text block, and that text is itself JSON holding url, status, text and json, with the scraped data under json. From a raw JSON-RPC response the path is result.content[0].text, parsed, then .json. A chat client unwraps that for you and code talking to the endpoint directly does not.

Handles, video ids and comment ids chain together. A profile links to its posts, every post carries its own video id for the comments tool, and every author in comments and search results carries a hasdataLink to its profile and a hasdataPostsLink to its videos. An agent walks from a keyword to a creator to a video to its comments without ever constructing a URL.

Get TikTok profile

hasdata_tiktok_profile_getTikTokProfile

One public account by handle.

Parameter

Type

Required

Notes

handle

string

yes

The username, with or without the leading @

Returns username, nickname, biography, bioLink, verified, language, createTime, the avatar URLs, and the followers, follows, likes, videos and friends counts as integers. The counts are already parsed, so followers > 1000000 compares numbers, not display strings.

A handle that does not exist still comes back with requestMetadata.status set to ok, the profile object simply absent. Check that the object is there before reading username or any other field, or an agent doing profile.username throws on nothing.

{
  "username": "mrbeast",
  "nickname": "MrBeast",
  "verified": true,
  "biography": "Checkout My New Book!👇",
  "bioLink": "http://themostdangerousgames.com",
  "createTime": "2018-10-20T19:26:16.000Z",
  "followers": 138387571,
  "follows": 354,
  "likes": 1427086888,
  "videos": 466,
  "friends": 285
}

Get TikTok posts

hasdata_tiktok_posts_getTikTokPosts

A page of an account's videos by handle, newest first.

Parameter

Type

Required

Notes

handle

string

yes

The username, with or without the leading @

nextPageToken

string

The pagination.nextPageToken from the previous response. Omit it for the first page

One call returns about thirty videos plus pagination, which carries hasMore and the nextPageToken you feed back to walk the account history one page at a time. Each video carries id, description, url, duration, the cover and playable video URLs, music, and the likes, comments, shares, plays, collects and reposts counts as integers.

hashtags and mentions are present only on videos that use them. In one real page of 27 videos, 4 carried a hashtags array and 10 carried mentions. Test for the key before you read it, rather than assuming every video has both.

{
  "id": "7677375185028271391",
  "description": "would you take the car or nah?",
  "url": "https://www.tiktok.com/@mrbeast/video/7677375185028271391",
  "createTime": "2026-08-23T23:36:59.000Z",
  "duration": 41,
  "likes": 129500,
  "comments": 6670,
  "shares": 2033,
  "plays": 1100000,
  "collects": 4986,
  "music": { "title": "original sound", "authorName": "MrBeast", "original": true }
}

Get TikTok comments

hasdata_tiktok_comments_getTikTokComments

The comments on a public video, or the replies under one comment.

Parameter

Type

Required

Notes

videoId

string

yes

The numeric id, the part after /video/ in a TikTok URL. Keep it a string. The id is a 64-bit number that loses its last digits if it ever passes through a JavaScript Number

commentId

string

Pass it to get the replies to that comment instead of the video's top-level comments. A string, for the same 64-bit reason as videoId

nextPageToken

string

Token from the previous response. Omit it for the first page

Each comment carries text, likes, createTime, replyCount and an author, and every author carries a hasdataLink to its profile and a hasdataPostsLink to its videos. pagination.total reports the video's whole comment count, so you know the depth before you page. A comment with a non-zero replyCount has replies you reach by calling again with its id as commentId.

{
  "id": "7677377150003053325",
  "text": "How could someone turn down a car",
  "createTime": "2026-08-23T23:45:06.000Z",
  "likes": 3802,
  "replyCount": 22,
  "author": {
    "username": "hohce.verggr",
    "nickname": "Sasori",
    "hasdataLink": "https://api.hasdata.com/scrape/tiktok/profile?handle=hohce.verggr",
    "hasdataPostsLink": "https://api.hasdata.com/scrape/tiktok/posts?handle=hohce.verggr"
  }
}

Search TikTok

hasdata_tiktok_search_getTikTokSearch

A keyword search over videos or creators.

Parameter

Type

Required

Notes

keyword

string

yes

The phrase to search for

type

string

video by default, or user to search creators

nextPageToken

string

Token from the previous response. Omit it for the first page

With type: video the response holds videos in the same shape the posts tool returns, each with its author. With type: user it holds creators, each with username, nickname, signature (the bio), avatarUrl, followers, and the same hasdataLink and hasdataPostsLink to chain into a profile or its videos. A verified flag is present on accounts that carry one.

{
  "username": "la.mooncoldbrew",
  "nickname": "lamoon cold brew coffee",
  "signature": "อยากได้สูตรชงเมนูไหน Comment ไว้เลยน้า",
  "followers": 48000,
  "hasdataLink": "https://api.hasdata.com/scrape/tiktok/profile?handle=la.mooncoldbrew",
  "hasdataPostsLink": "https://api.hasdata.com/scrape/tiktok/posts?handle=la.mooncoldbrew"
}

Errors and failure paths

Your client almost never sees an HTTP error code from a tool call. The MCP layer answers 200 and puts the failure inside the result, with isError set to true and the reason as text. The agent reads a message where you might expect a status line.

A wrong key surfaces as tool output, not as a failed connection. tools/list accepts any non-empty key and returns all four tools, so the client completes its handshake and shows green. The first tool call then comes back with isError: true and the text HasData API error: 401 Unauthorized. Watch for that string, because nothing earlier in the flow reports the problem.

A missing key is the one real HTTP error. Authorization runs before any tool, and the connection itself fails with 401. CORS headers are present, and a browser client reads the status and not an opaque network failure.

An argument that breaks a tool's schema is rejected before it becomes a scrape. The server answers with isError: true and the text MCP error -32602: Input validation error, naming the offending field. Nothing is fetched and nothing is charged.

A call that succeeds and finds nothing is the case that trips people up. A handle that does not exist comes back as an ordinary result with requestMetadata.status set to ok and the data key simply missing. Nothing in the body says the result was empty. Test for the field you need, not for an error.

An identifier the platform rejects returns 400 with requestMetadata.status set to error.

Results that carry data also carry a requestMetadata.id worth quoting in support.

Pricing, free tier and limits

Every TikTok tool costs 10 credits per successful call. Response size does not change the price. A full page of videos costs the same as a profile with one field.

The free tier is 1,000 credits every month with no card, which is 100 TikTok calls. It renews with the billing cycle, so a low-volume agent runs on the free tier indefinitely.

Paid plans start at $49 a month for 200,000 credits, which is 20,000 calls. The unit price falls with volume, from $2.45 per 1,000 calls on the entry plan to $0.99 on Business, $0.83 on Growth and $0.75 on the largest high-volume plans.

Your plan also sets concurrency. The free tier allows 1 request at a time, Startup 15, Business 30, Growth 50, and the high-volume plans run from 200 to 1,500. Handle the overflow case defensively in anything unattended, because an agent that fans out will reach the ceiling before you do.

A request that comes back non-200 is not billed. A successful call that finds nothing is still a call.

Tool selection

The apis query parameter decides which tools your agent sees. Fewer tools means less context spent on tool definitions, and fewer chances for the model to reach for the wrong one.

?apis=tiktok                     the four tools in this repo
?apis=tiktok,instagram           a social bundle
?apis=tiktok,google_serp         add Google search

The parameter takes provider names like tiktok and individual API names like tiktok_search. Misspelled names are ignored. If every name is wrong the request fails with 400, and the body lists both what it did not recognise and every valid value. Drop the parameter and the same endpoint exposes all 57 HasData tools.

How it compares

TikTok's own developer program does not cover general reading of public content. The Research API is gated behind an application and open to approved academic and nonprofit researchers in a limited set of regions. The Display API returns only the content of the account that signs in over OAuth. Neither fits an agent that needs to read an arbitrary public profile, its videos, or a video's comments.

Official TikTok APIs

This server

Access

Research API by application, or Display API for your own account

One key and one URL

Scope

Approved researchers, or your own authenticated account

Any public profile, video or search

Auth

Application review or OAuth

An x-api-key header

Comments of videos you do not own

Restricted

Yes, with reply threads

Setup

Developer account and approval

None

Writes and private data

Posting and your own account data over OAuth

Read-only, public data only

Most other TikTok MCP servers wrap a single unofficial endpoint. This one covers the four reads an agent actually chains, profile to posts to comments, plus search, so a whole research pass runs against one server.

What this server does not do. No posting, no direct messages, no follower-only or private content, no analytics for accounts you do not own. It reads what a signed-out visitor can see.

FAQ

Is there an official TikTok MCP server?

TikTok does not publish one. Every option is built by somebody else. This one is maintained by HasData and reads public pages, which is why it needs no TikTok developer account.

What is a TikTok MCP server?

A server that exposes TikTok data as tools an AI client can call. The client sends a tool call over the Model Context Protocol, the server fetches the data and returns structured JSON, and the model works with the result and never sees a page of HTML. This one exposes four tools and runs remotely. The client connects to a URL and starts no local process.

Do I need a TikTok API key or a developer account?

No. The only credential is your HasData key. There is no developer application to file and no OAuth consent screen, because the tools read public TikTok pages and not the TikTok developer APIs.

Do I need to host or run anything?

No. This is a remote MCP server on streamable HTTP. Nothing to install, no container to keep warm, no process to restart.

Is the data live or cached?

Live. Each call fetches at request time and carries its own requestMetadata.id. Counters like plays and likes track the page, so they move as the page moves.

Can I read a private account?

No. The tools return what a signed-out visitor sees. A private account's videos are not public, so they are not in any response.

Can I read comment replies, not just top-level comments?

Yes. Call the comments tool with a comment's id as commentId and it returns that comment's replies. A comment's replyCount tells you whether there are any.

Can I use this together with other HasData APIs?

Yes. The apis parameter takes a list, and ?apis=tiktok,instagram gives your agent the four TikTok tools plus Instagram. Drop the parameter and you get everything.

Compliance and personal data

HasData accesses publicly available data only. A platform's terms may restrict automated access, and you are responsible for your own compliance. Where the data you collect includes personal information, make sure you have a lawful basis for it under GDPR, CCPA or the equivalent rules in your jurisdiction.

Product page and request builder

TikTok Scraper API

Server documentation

MCP server docs

All 57 tools in one server

HasData/hasdata-mcp

Client walkthroughs

MCP clients and integrations

Everything else we scrape

TikTok Scraper API and 54 more

Plans and credit costs

Plans and credit costs

Keys and usage

HasData dashboard

Node launcher on npm

@hasdata/tiktok-mcp

Python launcher on PyPI

hasdata-tiktok-mcp

Development

This repository is configuration and documentation for a remote server. There is no build step and nothing to containerize.

The tests in test/ assert the tool contract, the part that can break without a commit here. They check that ?apis=tiktok returns exactly four tools, that every tool still declares its required parameter, that no name changed, and that the key in use is actually accepted. That last check calls a tool for real and costs 10 credits, which is the price of a canary that can fail for the right reason.

# macOS and Linux
HASDATA_API_KEY=your_key_here npm test

# Windows PowerShell
$env:HASDATA_API_KEY="your_key_here"; npm test

The same suite runs in CI on every push and once a week on a schedule, because the upstream tool list can change without anyone touching this repository. A failure means the tool list moved, the key stopped working, or the endpoint was unreachable, and the assertion message says which.

Contributing

Corrections to the tool tables and the response samples are the most useful contribution, because those are the parts that drift. Include the call you made and the response you got. Pull requests from forks run the suite without a key, and the live checks skip instead of going red.

License

MIT. See LICENSE.

Available Tools

4 tools
hasdata_tiktok_comments_getTikTokCommentstiktok_comments: GET /AInspect

Get TikTok Comments

Fetches the comments on a public TikTok video by its numeric video id, or the replies to a specific comment when commentId is given. Each comment returns text, like count, timestamp, reply count, and author (username, nickname, avatar, plus hasdataLink to the profile endpoint and hasdataPostsLink to the posts endpoint). Supports token-based pagination via nextPageToken. Use for sentiment analysis, engagement research, or building comment datasets from a video discovered via the posts or search APIs.

ParametersJSON Schema
NameRequiredDescriptionDefault
videoIdYesThe numeric id of the video (the number after `/video/` in a TikTok URL).
commentIdNoWhen provided, returns the replies to this comment instead of the video's top-level comments.
nextPageTokenNoDefines the next page token. Use the `nextPageToken` value returned by the previous response. Omit it to fetch the first page.

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden and explains read-only fetching of public comments, pagination via nextPageToken, and the returned comment fields. It does not mention rate limits or error behavior, but the disclosed behavior is clear.

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 compact, well-organized, and free of filler. Key information about input, output fields, pagination, and use cases is front-loaded.

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?

Although there is no output schema, the description enumerates returned comment fields and pagination behavior, which gives an agent enough context for typical use. It lacks response envelope or error details, but those are not essential for selection.

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?

All parameters have descriptive schema entries, and the description adds practical context: videoId is the number after /video/ in a TikTok URL, commentId selects replies, and nextPageToken uses the previous response value with omission for the first page.

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?

Clearly states it fetches TikTok comments by video ID or replies by comment ID, distinguishing it from sibling TikTok profile, posts, and search tools. The verb 'Fetches' and the resource 'comments on a public TikTok video' make the purpose specific.

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?

Provides concrete use cases such as sentiment analysis, engagement research, and building comment datasets, and notes that videos may be discovered via posts or search APIs. It does not explicitly contrast with sibling tools, but the guidance is sufficient for typical selection.

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

hasdata_tiktok_posts_getTikTokPoststiktok_posts: GET /AInspect

Get TikTok Posts

Fetches a page of videos for a public TikTok account by username (handle) and returns each video with description, hashtags, mentions, like/comment/share/play/collect counts, cover and playable video URLs, music, duration, and timestamp. Returns a page of ~35 videos plus a nextPageToken; pass that token back to walk the account history one page at a time. Use to monitor competitor content, track engagement of creator videos, or build datasets of account content for vetting and analytics.

ParametersJSON Schema
NameRequiredDescriptionDefault
handleYesThe TikTok username of the account whose videos you want to scrape, with or without the `@` symbol.
nextPageTokenNoDefines the next page token. It is used for retrieving the next page of results. Use the `nextPageToken` value returned by the previous response. Omit it to fetch the first page.

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses pagination via nextPageToken, a page size of ~35 videos, and the public-account constraint. It does not mention rate limits or error cases, but the read-only nature is clearly implied by 'Fetches'.

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?

The description is dense and front-loaded, with the core behavior stated immediately and use cases at the end. The opening line repeats the title, but the rest of the content 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?

For a simple two-parameter fetch tool with no output schema, the description covers what is returned, pagination, and typical use cases. It is complete enough for correct invocation, though it omits potential failure modes and rate-limit context.

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%, and both parameters are already well-documented in the schema. The description reinforces the handle and pagination concepts but does not add significant meaning beyond 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 clearly states the tool fetches a page of videos for a public TikTok account by username, and enumerates the returned fields. This distinguishes it from sibling tools focused on comments, profile, and 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?

Explicit use cases are given: monitoring competitors, tracking engagement, and building datasets for analytics. It does not name alternative tools or exclusions, but the context is clear enough for selecting this tool over the siblings.

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

hasdata_tiktok_profile_getTikTokProfiletiktok_profile: GET /AInspect

Get TikTok Profile

Fetches a public TikTok profile by username (handle) and returns nickname, biography, bio link, avatar URLs, verified/private flags, account creation time, and followers, follows, likes, videos, and friends counts. Use to enrich CRM/lead records, verify influencer reach before outreach, monitor competitor accounts, or build datasets of creator metadata for vetting and analytics.

ParametersJSON Schema
NameRequiredDescriptionDefault
handleYesThe TikTok username of the profile you want to scrape, with or without the `@` symbol.

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the full behavioral burden. It accurately conveys that this is a read operation (fetches) on public profiles, but it does not disclose potential edge cases like errors for non-existent handles, rate limits, or authentication requirements. For a simple GET it is acceptable but not exhaustive.

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?

The description is compact, front-loaded with the tool's purpose, and avoids unnecessary fluff. The second sentence adds value by listing return fields and use cases. It is efficiently written without waste.

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?

For a single-parameter tool with no output schema, the description covers the essential information: what it does, what it returns, and typical use cases. It does not discuss error handling or output formatting, but given the simplicity of the operation, it is sufficiently complete for an agent to invoke it.

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 single parameter 'handle' is fully documented in the schema with an explanation of format (with or without '@'). The description adds no additional semantics beyond restating the parameter name. Since schema coverage is 100%, the baseline of 3 applies.

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 it fetches a public TikTok profile by username and enumerates the exact data returned (nickname, bio, counts, flags). It is specific about the resource and action, and its distinctness from sibling tools (comments, posts, search) is evident from the resource type.

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 clear usage contexts (CRM enrichment, influencer vetting, competitor monitoring) which implicitly distinguish it from siblings that handle posts, comments, or search. It does not explicitly state when not to use it or name alternatives, but the context is unambiguous enough for an agent to select it correctly.

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

hasdata_tiktok_search_getTikTokSearchtiktok_search: GET /AInspect

Search TikTok

Searches TikTok by keyword and returns either videos (with description, hashtags, mentions, like/comment/share/play counts, cover and playable video URLs, music, and author) or users (nickname, bio, avatar, verified flag, follower count). Each author and each user carries a hasdataLink to their profile endpoint and a hasdataPostsLink to their posts endpoint. Supports token-based pagination via nextPageToken. Use for content discovery, trend research, influencer discovery, or building datasets from a keyword.

ParametersJSON Schema
NameRequiredDescriptionDefault
typeNoWhat to search for — videos or users. Defaults to video.
keywordYesThe phrase to search for on TikTok.
nextPageTokenNoDefines the next page token. Use the `nextPageToken` value returned by the previous response. Omit it to fetch the first page.

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description should carry the full burden of disclosing behavioral traits. It does not state that the operation is read-only, nor does it mention rate limits, data modification, or other side effects. The absence of such details leaves behavioral transparency incomplete.

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?

The description is moderately concise and well-structured. It conveys the core functionality and relevant details without unnecessary verbosity, though it could be slightly tighter by removing redundant phrasing like repeating 'hasdataLink' and 'hasdataPostsLink'.

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?

Given the absence of an output schema, the description does well to enumerate the return fields (e.g., description, likes, comments, author) and explain pagination. It also gives practical use cases. Minor gaps include not explaining the structure of the nested author/user objects or the exact format of the response envelope.

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 covers all parameters with descriptions (100% coverage), and the tool description adds some context about pagination usage. However, it largely repeats the schema information without significantly deepening understanding, so it provides marginal added value.

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 searches TikTok by keyword and returns videos or users, with a list of fields. It also names specific use cases like content discovery and trend research, making the purpose unambiguous.

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 guidance on when to use the tool (content discovery, trend research, etc.) and explains pagination with nextPageToken. However, it does not explicitly contrast with sibling tools, though the distinct focus on search is implicit.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 4 tool updatesv0.1.0
    • First observedhasdata_tiktok_comments_getTikTokComments
    • First observedhasdata_tiktok_posts_getTikTokPosts
    • First observedhasdata_tiktok_profile_getTikTokProfile
    • First observedhasdata_tiktok_search_getTikTokSearch

TDQS

A4.2/5.0

Scored across 4 tools

Disambiguation5/5

Each tool targets a distinct data surface: search, profile metadata, account posts, and comments. Even though profile and posts are both keyed by username, their return shapes are clearly different, so an agent should not confuse them.

Naming Consistency5/5

Every tool follows the same strict pattern: hasdata_tiktok_<resource>_getTikTok<Resource>. The verb-first camelCase naming is applied uniformly across the entire set.

Tool Count5/5

Four tools is a focused, appropriate scope for a read-only TikTok data server. Each tool covers a distinct public-data API surface and none feel redundant.

Completeness4/5

The set covers the main public TikTok use cases: discovery via search, profile lookup, posts retrieval, and comment fetching. A direct get-video-by-ID tool is missing, but search and posts largely fill that gap.

Maintenance

ActivityMaintained
ResponsivenessNo issues

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