Public TikTok profiles, videos, comments and keyword search as JSON. No developer account.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
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.
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.
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.
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:
Python instead of Node? Swap the launcher for the PyPI package, which uvx runs without a manual install:
~/.cursor/mcp.json for every project, or .cursor/mcp.json for one:
~/.codeium/windsurf/mcp_config.json. Windsurf calls the field serverUrl, not url:
.vscode/mcp.json in the workspace:
~/.codex/config.toml:
~/.gemini/settings.json:
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 trial goes further on narrow questions than on open-ended crawls.
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.
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.statusset took, theprofileobject simply absent. Check that the object is there before readingusernameor any other field, or an agent doingprofile.usernamethrows on nothing.
hasdata_tiktok_posts_getTikTokPosts
A page of an account's videos by handle, newest first.
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