Pricing

$0.40 / 1,000 tweets

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🏯 Tweet Scraper V2 (Pay Per Result) - X / Twitter Scraper

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Developed by

API Dojo

⚡️ Lightning-fast search, URL, list, and profile scraping, with customizable filters. At $0.40 per 1000 tweets, and 30-80 tweets per second, it is ideal for researchers, entrepreneurs, and businesses! Get comprehensive insights from Twitter (X) now!

3.0 (66)

Pricing

$0.40 / 1,000 tweets

680

Total users

16K

Monthly users

1.9K

Runs succeeded

>99%

Issues response

4.5 hours

Last modified

5 hours ago

Social media

Lead generation

You can access the 🏯 Tweet Scraper V2 (Pay Per Result) - X / Twitter Scraper 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": {
        "local-actors-mcp-server": {
            "command": "npx",
            "args": [
                "-y",
                "@apify/actors-mcp-server",
                "--actors",
                "apidojo/tweet-scraper"
            ],
            "env": {
                "APIFY_TOKEN": "<YOUR_API_TOKEN>"
            }
        }
    }
}

Configure MCP server with 🏯 Tweet Scraper V2 (Pay Per Result) - X / Twitter Scraper

You can interact with the MCP server via standard input/output - stdio (as shown above), which is ideal for local integrations and command-line tools such as the Claude desktop client, or you can interact with the server through Server-Sent Events (SSE) to send messages and receive responses, which looks as follows:

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

You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other supported 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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