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Pinterest Comments Scraper βœ¨πŸ“ŒπŸ’¬

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Pinterest Comments Scraper βœ¨πŸ“ŒπŸ’¬

Pinterest Comments Scraper βœ¨πŸ“ŒπŸ’¬

scrapestorm/pinterest-comments-scraper
Try for free

2 hours trial then $9.90/month - No credit card required now

Pinterest Comments Scraper πŸ’¬πŸ“ŒπŸ” allows you to extract detailed comments from Pinterest posts. With customizable filters and in-depth data extraction, you can easily gather the insights needed for your projects! πŸŒŸβœ¨πŸ“

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  • Created in Jan 2025

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You can access the Pinterest Comments Scraper βœ¨πŸ“ŒπŸ’¬ 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.

1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=scrapestorm/pinterest-comments-scraper"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Pinterest Comments Scraper βœ¨πŸ“ŒπŸ’¬ via Model Context Protocol (MCP) server

MCP server lets you use Pinterest Comments Scraper βœ¨πŸ“ŒπŸ’¬ within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Pinterest Comments Scraper βœ¨πŸ“ŒπŸ’¬ Actor with the provided input.

1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2  "jsonrpc": "2.0",
3  "id": 1,
4  "method": "tools/call",
5  "params": {
6    "arguments": {
7      "post_url": "https://jp.pinterest.com/pin/636977941054343221/",
8      "maxcomments": 30
9},
10    "name": "scrapestorm/pinterest-comments-scraper"
11  }
12}'

The response should be: Accepted. You should received response via SSE (JSON) as:

1event: message
2data: {
3  "result": {
4    "content": [
5      {
6        "type": "text",
7        "text": "ACTOR_RESPONSE"
8      }
9    ]
10  }
11}

Configure local MCP Server via standard input/output for Pinterest Comments Scraper βœ¨πŸ“ŒπŸ’¬

You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:

1{
2  "mcpServers": {
3    "actors-mcp-server": {
4      "command": "npx",
5      "args": [
6        "-y",
7        "@apify/actors-mcp-server",
8        "--actors",
9        "scrapestorm/pinterest-comments-scraper"
10      ],
11      "env": {
12        "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13      }
14    }
15  }
16}

You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.

To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.