You can access the Actor Testing 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

$# Start Server-Sent Events (SSE) session and keep it running
<curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=pocesar/actor-testing"

# Session id example output:
# event: endpoint
# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Actor Testing via Model Context Protocol (MCP) server

MCP server lets you use Actor Testing 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 Actor Testing 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": {
$      "testSpec": "({ it, xit, moment, _, run, expect, expectAsync, input, describe }) => {\\n    (input.resource ? [\\n        '\''beta'\'',\\n    ] : [\\n        '\''latest'\'',\\n    ]).forEach((build) => {\\n        describe(`${build} version`, () => {\\n            it('\''test something-task'\'', async () => {\\n                const runResult = await run({\\n                    taskId: '\'''\'',\\n                });\\n\\n                await expectAsync(runResult).toHaveStatus('\''SUCCEEDED'\'');\\n                await expectAsync(runResult).withLog((log) => {\\n                    expect(log)\\n                        .withContext(runResult.format('\''ReferenceError'\''))\\n                        .not.toContain('\''ReferenceError'\'');\\n                    expect(log)\\n                        .withContext(runResult.format('\''TypeError'\''))\\n                        .not.toContain('\''TypeError'\'');\\n                });\\n\\n                await expectAsync(runResult).withStatistics((stats) => {\\n                    expect(stats.requestsRetries)\\n                        .withContext(runResult.format('\''Request retries'\''))\\n                        .toBeLessThan(3);\\n\\n                    expect(stats.crawlerRuntimeMillis)\\n                        .withContext(runResult.format('\''Run time'\''))\\n                        .toBeWithinRange(0.1 * 60000, 10 * 60000);\\n                });\\n\\n                await expectAsync(runResult).withDataset(({ dataset, info }) => {\\n                    expect(info.cleanItemCount)\\n                        .withContext(runResult.format('\''Dataset cleanItemCount'\''))\\n                        .toBeGreaterThan(0);\\n\\n                    expect(dataset.items)\\n                        .withContext(runResult.format('\''Dataset items array'\''))\\n                        .toBeNonEmptyArray();\\n                });\\n            });\\n        });\\n    });\\n}",
$      "slackChannel": "#public-actors-tests-notifications",
$      "slackPrefix": "@lead-dev @actor-owner"
$},
$    "name": "pocesar/actor-testing"
$  }
$}'

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 Actor Testing

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",
        "pocesar/actor-testing"
      ],
      "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.

test actor

elxin/test-actor

InvoUp

Test Actor

godofpotato/test-actor

This is a test actor do not use it!

Emir Yılmaz

Log Scanner

lukaskrivka/log-scanner

Log scanner helps you to find particular text in your log files. It can scan [Apify](https://apify.com/) runs, tasks, or actors but also arbitrary text files. If you ever had a problem finding that one error in a thousand runs, this is a tool to use.