You can access the dummy-actor 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/?tools=knowing_didgeridoo/dummy-actor",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with dummy-actor

Get a ready-to-use configuration for your MCP client with the dummy-actor Actor preconfigured at mcp.apify.com?tools=knowing_didgeridoo/dummy-actor .

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.

My Actor 2

accommodating_swimsuit/my-actor-2

The second best actor.

filip_alias

My Actor

accommodating_swimsuit/my-actor

This is the best actor in the universe.

filip_alias

My Actor 1

flattered_kettle/my-actor-1

This is the best actor in the world.

Filip Cicvárek

Example actor paid per result

mhamas/example-actor-paid-per-result

This is an example actor demonstrating "pay per result" model. When you run this actor, you are only charged for the results it produces, not for the underlying platform usage.