Pricing

$0.30 / 1,000 posts

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🏯 Tiktok Location Scraper (Pay Per Result)

Try for free

Developed by

API Dojo

Kudos to the exceptional TikTok Location Scraper, the champion in speed, cost-effectiveness, and efficiency for extracting location-based posts from TikTok.com. Retrieve any post that is tagged on any location at a blazing-fast speed! Extremely cheap and perfectly suitable for all needs.

5.0 (1)

Pricing

$0.30 / 1,000 posts

Issues response

0.31 hours

Last modified

20 hours ago

Lead generation

Social media

You can access the 🏯 Tiktok Location Scraper (Pay Per Result) programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?actors=apidojo/tiktok-location-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with 🏯 Tiktok Location Scraper (Pay Per Result)

You have a few options for interacting with the MCP server:

Use mcp.apify.com via mcp-remote from your local machine to connect and authenticate using OAuth or an API token (as shown in the JSON configuration above).
Set up the connection directly in your MCP client UI by providing the URL https://mcp.apify.com/?actors=apidojo/tiktok-location-scraper along with an API token (or use OAuth).
Connect to mcp.apify.com via Server-Sent Events (SSE), as shown below:

{
    "mcpServers": {
        "apify": {
            "type": "sse",
            "url": "https://mcp.apify.com/?actors=apidojo/tiktok-location-scraper",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other MCP client of your choice.

If you want to learn more about our Apify MCP implementation, check out our MCP documentation. To learn more about the Model Context Protocol in general, refer to the official MCP documentation or read our blog post.

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