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Otto Product Scraper

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Otto Product Scraper

Otto Product Scraper

muhammetakkurtt/otto-product-scraper
Try for free

1 day trial then $24.99/month - No credit card required now

An efficient actor to extract product information from Otto.de. This scraper collects details like product name, price, brand, image URL, and ratings based on a given search term. It allows users to specify the number of pages to scrape and saves data to Apify's dataset for easy access and analysis.

You can access the Otto Product Scraper programmatically from your own applications by using the Apify API. You can 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
2curl https://actors-mcp-server.apify.actor/sse?token=<APIFY_TOKEN>
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Otto Product Scraper via Model Context Protocol (MCP) server

MCP server lets you use Otto Product Scraper 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 Otto Product Scraper 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": {  # Actor inputs
7        "searchTerm": ...,
8        ...
9    },
10    "name": "l5mwTJWPVcwsCTHKz"
11  }
12}'

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

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

Configure local MCP Server via standard input/output for Otto Product Scraper

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", "@apify/actors-mcp-server",
7      "--actors", "l5mwTJWPVcwsCTHKz"
8    ],
9    "env": {
10       "APIFY_TOKEN": "YOUR_API_TOKEN"
11    }
12  }
13}
14}

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.

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  • >99% runs succeeded

  • Created in Oct 2024

  • Modified 5 months ago