Linkedin Posts Informations Scraper

Pricing

$30.00/month + usage

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Linkedin Posts Informations Scraper

Try for free

Developed by

SASWAVE

Maintained by Community

Scrape linkedin posts from linkedin post search results, url post or linkedin member. Supports advanced linkedin search filters. Extract posts data at scale.

4.7 (5)

Pricing

$30.00/month + usage

732

Issues response

13 hours

Last modified

a month ago

Automation

Lead generation

You can access the Linkedin Posts Informations 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": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?actors=saswave/linkedin-posts-informations-parser",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with Linkedin Posts Informations Scraper

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=saswave/linkedin-posts-informations-parser 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=saswave/linkedin-posts-informations-parser",
            "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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