Website Checker Workload
Pricing
Pay per usage
Website Checker Workload
Creates reasonable workloads for analyzing any website with the Website Checker actor and combines the resulting data. This is the easiest way to analyze any website for compute unit usage and anti-scraping blocking.
0.0 (0)
Pricing
Pay per usage
2
Total users
27
Monthly users
1
Runs succeeded
>99%
Last modified
2 years ago
You can access the Website Checker Workload 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.
$# Start Server-Sent Events (SSE) session and keep it running<curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=lukaskrivka/website-checker-workload"
# Session id example output:# event: endpoint# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1faUsing Website Checker Workload via Model Context Protocol (MCP) server
MCP server lets you use Website Checker Workload 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 Website Checker Workload Actor with the provided input.
$curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{$ "jsonrpc": "2.0",$ "id": 1,$ "method": "tools/call",$ "params": {$ "arguments": {$ "website": "https://apify.com",$ "proxyGroups": [$ "auto",$ "BUYPROXIES84958"$ ]$},$ "name": "lukaskrivka/website-checker-workload"$ }$}'The response should be: Accepted. You should received response via SSE (JSON) as:
$event: message$data: {$ "result": {$ "content": [$ {$ "type": "text",$ "text": "ACTOR_RESPONSE"$ }$ ]$ }$}Configure local MCP Server via standard input/output for Website Checker Workload
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:
{ "mcpServers": { "actors-mcp-server": { "command": "npx", "args": [ "-y", "@apify/actors-mcp-server", "--actors", "lukaskrivka/website-checker-workload" ], "env": { "APIFY_TOKEN": "<YOUR_API_TOKEN>" } } }}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.
