You can access the Monitoring Runner 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=apify/monitoring-runner"

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

Using Monitoring Runner via Model Context Protocol (MCP) server

MCP server lets you use Monitoring Runner 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 Monitoring Runner 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": {
$      "limit": 1000,
$      "checkersInput": {
$            "RESOURCE_STATS_CHECKER": {},
$            "DEDUPLICATION_CHECKER": {
$                  "uniqueKey": "email"
$            },
$            "SCHEMA_VALIDATOR_CHECKER": {
$                  "options": [
$                        {
$                              "resourceList": [
$                                    "id",
$                                    "id"
$                              ],
$                              "resourceRegex": "",
$                              "minItemCount": 100,
$                              "maxItemCount": 5000,
$                              "validationSchema": "{ address: String, open: Boolean }"
$                        }
$                  ]
$            }
$      },
$      "reportersInput": {
$            "EMAIL_REPORTER": {
$                  "sendMailInput": {
$                        "to": "info@apify.com",
$                        "subject": "My monitoring task report"
$                  }
$            },
$            "SLACK_REPORTER": {
$                  "slackInput": {
$                        "token": "Your token",
$                        "message": "Hey, look what I have done!",
$                        "channel": "#monitoring"
$                  }
$            },
$            "DASHBOARD_REPORTER": {
$                  "notifyOnUpdate": true
$            }
$      }
$},
$    "name": "apify/monitoring-runner"
$  }
$}'

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 Monitoring Runner

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",
        "apify/monitoring-runner"
      ],
      "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.

Monitoring Checker Stats

apify/monitoring-checker-stats

The monitoring checker stats is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

4.8

Monitoring Checker Run Status

apify/monitoring-checker-run-status

The monitoring checker run status is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

4.8

Monitoring Teardown

apify/monitoring-teardown

The monitoring teardown is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

5.0

Monitoring Checker Schema

apify/monitoring-checker-schema

The monitoring checker schema is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

4.8

Monitoring Checker Duplication

apify/monitoring-checker-duplication

The Monitoring checker duplication is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

4.8

Monitoring Reporter Slack

apify/monitoring-reporter-slack

The Monitoring reporter slack is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

4.3

Monitoring Reporter Mail

apify/monitoring-reporter-mail

The Monitoring reporter mail is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

4.3

Monitoring Reporter Dashboard

apify/monitoring-reporter-dashboard

The monitoring reporter dashboard is a part of the Apify Monitoring Suite (apify/monitoring). See its readme for more information and how to use this.

Apify

4.8

Website Checker Runner Puppeteer

lukaskrivka/website-checker-puppeteer

Checks the provided website using Puppeteer. This is a low level runner, most likely you want to use the high level master actor - https://apify.com/lukaskrivka/website-checker

Lukáš Křivka

194

Website Checker Runner Playwright

lukaskrivka/website-checker-playwright

Checks the provided website using Playwright. This is a low level runner, most likely you want to use the high level master actor - https://apify.com/lukaskrivka/website-checker

Lukáš Křivka

132