Pricing

Pay per usage

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Failed Runs Monitor

Try for free

Developed by

Jan Novotný

This actor will let you know about failed or time outed runs of your actors and tasks via Slack or email. It can also notice you about successful runs with empty dataset, check JSON schema of dataset items, or about runs that are running for too long.

0.0 (0)

Pricing

Pay per usage

Total users

Monthly users

Runs succeeded

>99%

Last modified

3 months ago

Automation

Open source

You can access the Failed Runs Monitor 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/sse?actors=jannovotny/failed-runs-monitor",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with Failed Runs Monitor

You have a few options for interacting with the MCP server:

Use mcp.apify.com via mcp-remote from your local machine to connect and authenticate using OAuth or an API token (as shown in the JSON configuration above).
Set up the connection directly in your MCP client UI by providing the URL https://mcp.apify.com/sse?actors=jannovotny/failed-runs-monitor along with an API token (or use OAuth).
Connect to mcp.apify.com via Server-Sent Events (SSE), as shown below:

{
    "mcpServers": {
        "apify": {
            "type": "sse",
            "url": "https://mcp.apify.com/sse?actors=jannovotny/failed-runs-monitor",
            "headers": {
                "Authorization": "Bearer <YOUR_API_TOKEN>"
            }
        }
    }
}

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.

Details of runs

useful-tools/details-of-runs

This Actor is capable to list and store your Runs into the Dataset with all the necessary Run related details (like stats, usage, current pricing).

Useful tools

Slack Message Generator

katerinahronik/slack-message

This actor sends messages to Slack automatically. It can be used instead of email notifications and is ideal to combine with other actors monitoring successful runs, errors, etc.

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Validate Dataset(s) with JSON Schema

jaroslavhejlek/validate-dataset-with-json-schema

This Actor validates items in one or more datasets against a provided JSON Schema. Use it if you planning to add a dataset validation schema to your actor and you want test it.

Jaroslav Hejlek

Rebirth failed requests

lukaskrivka/rebirth-failed-requests

Rebirth failed requests of past runs into a pristine state with no retries so you can rescrape them by resurrecting the run.

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Append to dataset

valek.josef/append-to-dataset

Utility actor that allows you to build a single large dataset from individual default datasets of other actor runs.

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Restore failed requests

onidivo/restore-failed-requests

Restore failed requests of a run from the dataset to the request queue.

Onidivo Technologies

Actor Probe

cyberfly/actor-probe

Reports performance stats of any actor calculated from its runs on a daily and weekly basis. Notification will be skipped if no new runs are found since the last report.

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Facebook Video Search Scraper

apify/facebook-video-search-scraper

Extract Facebook data from videos that match your search query. Export scraped data, run the scraper via API, schedule and monitor runs, or integrate with other tools.

Apify

110

4.2

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.

Lukáš Křivka