You can access the Rebirth failed requests 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/?actors=lukaskrivka/rebirth-failed-requests",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

Configure MCP server with Rebirth failed requests

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/?actors=lukaskrivka/rebirth-failed-requests 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/?actors=lukaskrivka/rebirth-failed-requests",
            "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.

Restore failed requests

onidivo/restore-failed-requests

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

Onidivo Technologies

Failed Runs Monitor

jannovotny/failed-runs-monitor

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.

Jan Novotný

Actor fail manager

lukaskrivka/actor-fail-manager

Automatically triggered on a failed run to analyze if the run should be resurrected and to create an error report for the author.

Lukáš Křivka

33K

Linkedin Network Requests - List / Add / Remove

saswave/linkedin-network-requests---list-add-remove

SEND / REMOVE / LIST batch of linkedin connection requests. Recommended to call the actor once a day when ADDing. The script has a hard limit of 20 successfull connections requests per run. Linkedin has weekly limits setup (100-200) recommended usage: One run per day with 15-20 automated connection

SASWAVE

5.0

api-gw-lite

amernas/api-gw-lite

This actor serves as a proxy that accepts requests with custom field names and translates them to standard HTTP requests to target APIs. It's designed to work seamlessly on the Apify platform while also supporting local testing

Traffic Architect

Instagram Profile Posts Scraper

perfectscrape/mass-instagram-profile-posts-scraper

Super fast Instagram scraper, hundreds of requests per minute - using direct HTTP requests (no browser). Add multiple usernames/profile links. Get captions, images, videos, likes, comments, timestamps, and more. Fast, lightweight, low-cost—perfect for mass instagram scraping.

Sadnan

5.0

Linkedin Contacts CSV Uploader

big-brain.io/linkedIn-contacts-uploader

Send connection requests and bypass Linkedin's new limits by importing a Google Sheet or public CSV with email addresses. Go from 100 connection requests per week to 1000 per day.

Big Brain

Restart run

onidivo/restart-run

Restart a run by aborting it then resurrecting it. Mainly used when the run stuck for a long time.

Onidivo Technologies

Deep URL Content Crawler

6sigmag/deep-url-content-crawler

Scrape Failed Killer! A high-performance web scraper that rapidly extracts and analyzes content from multiple URLs simultaneously. Perfect for competitive research, content aggregation, and website structure analysis.