# Tiktok Search Suggestion Scraper (`topaz_sharingan/tiktok-search-suggestion-scraper`) Actor

Extract TikTok’s search autocomplete suggestions at scale to enhance keyword research, SEO, and content planning

- **URL**: https://apify.com/topaz\_sharingan/tiktok-search-suggestion-scraper.md
- **Developed by:** [Moses Ceaser](https://apify.com/topaz_sharingan) (community)
- **Categories:** AI, SEO tools, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## TikTok Search Suggestions Scraper | Extract TikTok Autocomplete Keywords

Pull TikTok's **search autocomplete suggestions** for any keyword — the exact phrases TikTok recommends as users type. No browser automation, no logins, no manual scrolling. Just paste one or more search terms, pick a region, and get structured JSON keyword data in seconds.

⭐ Fast & Reliable | � Region Targeting | � Bulk Query Support

***

### What Is This Actor?

This Apify actor extracts **TikTok search autocomplete suggestions** for any query. Perfect for keyword research, SEO, content ideation, trend discovery, and hashtag strategy.

Drop in a single keyword for a quick check or a list of seed terms to build a full keyword map — the scraper handles each query and writes one row per suggestion.

***

### What Data Can You Extract?

The scraper outputs **one row per suggestion**, so the dataset is ready for direct CSV / Excel / Sheets export. Each row contains:

| Field        | Description                                                     |
| ------------ | --------------------------------------------------------------- |
| `searchTerm` | The search term you queried (lets you join rows back to source) |
| `region`     | Region code used for the request (e.g. `US`)                    |
| `text`       | The suggested search phrase returned by TikTok                  |
| `position`   | Rank of the suggestion in the autocomplete list (0-based)       |
| `language`   | Detected language of the suggestion (e.g. `en`, `vi`)           |
| `score`      | Relevance score TikTok assigns to the suggestion                |

***

### Use Cases

- � **Keyword Research** — Discover the exact phrases TikTok suggests for your seed terms.
- � **SEO & Content Ideation** — Turn autocomplete data into video topics and captions.
- � **Hashtag & Trend Strategy** — Spot rising phrases and language variations early.
- 🌍 **Localization** — Compare suggestions across regions and languages.
- 🤖 **Keyword Maps & AI** — Feed structured suggestion data into clustering or LLM pipelines.
- 📊 **CSV / Sheets Export** — Flat one-row-per-suggestion output drops cleanly into spreadsheets.

***

### Input Parameters

| Parameter     | Type   | Description                                                       | Default    |
| ------------- | ------ | ----------------------------------------------------------------- | ---------- |
| `searchTerms` | Array  | List of search terms to fetch TikTok suggestions for.             | *Required* |
| `region`      | String | Region code used to localize suggestions (e.g. `US`, `GB`, `VN`). | `US`       |

> **Tip:** Each entry in `searchTerms` can be a plain string (`cats`) or an object (`{ "searchTerm": "cats" }`).

***

### How to Use

#### 1. Single Query

```json
{
  "searchTerms": ["cats"],
  "region": "US"
}
```

#### 2. Multiple Queries

```json
{
  "searchTerms": ["cats", "funny cats", "street food"],
  "region": "US"
}
```

***

### Output Example

Each suggestion is its own dataset row — perfect for tables, CSV exports, and downstream pipelines.

```json
{
  "searchTerm": "cats",
  "region": "US",
  "text": "cats funny video",
  "position": 0,
  "language": "en",
  "score": 0.03659618
}
```

### FAQ

**Can I scrape multiple keywords at once?**
Yes — add multiple terms to the `searchTerms` array. Each one is processed sequentially with a short delay to avoid rate limiting.

**How many suggestions are returned per query?**
TikTok typically returns around 10 autocomplete suggestions per search term, and every suggestion is written as its own dataset row.

**How do I know which keyword each suggestion belongs to?**
Every row contains a `searchTerm` field with the term you searched, so the dataset stays joinable even when you batch many keywords.

### Need Help?

Open an issue on the Apify platform or email: **topazsharingan9@gmail.com** — we respond within 24 hours. ⚡

# Actor input Schema

## `searchTerms` (type: `array`):

List of search terms to fetch TikTok autocomplete suggestions for (e.g. dogs, funny cats).

## `region` (type: `string`):

Region code used to localize suggestions (e.g. US, GB, VN).

## Actor input object example

```json
{
  "searchTerms": [
    "dogs"
  ],
  "region": "US"
}
```

# Actor output Schema

## `suggestions` (type: `string`):

All scraped TikTok search suggestions (search term, region, suggestion text, position, language, score).

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchTerms": [
        "dogs"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("topaz_sharingan/tiktok-search-suggestion-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "searchTerms": ["dogs"] }

# Run the Actor and wait for it to finish
run = client.actor("topaz_sharingan/tiktok-search-suggestion-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchTerms": [
    "dogs"
  ]
}' |
apify call topaz_sharingan/tiktok-search-suggestion-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,topaz_sharingan/tiktok-search-suggestion-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/TBHfa9lWg8cxMEv18/builds/4E3WAoB6hTXn83CI6/openapi.json