We have been using Apify for several months and the results have exceeded expectations. The Actor model abstracts away all the messy infrastructure, including proxies, retries, captcha solving, and data storage, so our developers focus on what matters rather than fighting UI changes from social media platforms every week. The MCP server integration is genuinely a game changer, letting Claude call Apify Actors as native tools and return structured results directly into the conversation. Scheduling, webhooks, and dataset APIs work reliably and integrations with data warehouses like Snowflake and BigQuery via Airbyte make it easy to pipe scraped data into our existing analytics stack. Highly recommended for any team serious about web data at scale. Review collected by and hosted on G2.com.

Pricing transparency is poor with no real-time spend alerts, the Actor Store feels cluttered making it hard to identify the most reliable options, and some advanced features like custom proxy configuration have a steep learning curve for newer users. Review collected by and hosted on G2.com.

What I like most is the flexibility of the platform. I use Playwright Actors, scheduling, datasets, and integrations to automate data collection for travel websites and Telegram workflows.

Once everything is configured, the automation runs reliably without needing to maintain my own servers. It has saved me many hours of manual work and made it much easier to manage recurring scraping tasks. Review collected by and hosted on G2.com.

The biggest challenge is the learning curve. If you are new to web scraping or automation, it takes some time to understand Actors, proxies, datasets, and all the available options.

Pricing can also become expensive for larger projects if they are not optimized. However, once I learned how to optimize my Actors, the platform became much more cost-effective. Review collected by and hosted on G2.com.

I really like that once the data is downloaded with Apify, I can integrate it with various programs like Gephi to analyze interaction networks or in geographic information systems like QGIS and some qualitative data analysis projects like Atlas.TI. This allows me to have a clear understanding of what I am analyzing. Additionally, I appreciate that it is really easy to set up, not complicated, it was very intuitive. The platform is very useful for academic research and sociodigital network analysis, and what I value most is the wide variety of actors available that allows me to obtain structured data without developing a scraper from scratch for each project. Review collected by and hosted on G2.com.

Let's say that the only problem I have is that there are so many actors that it's difficult to select which one is the right one. Review collected by and hosted on G2.com.

The Actor marketplace is incredibly valuable. I'm building an automated lead generation system using AI (Claude API for scoring, Playwright for automation) and Apify handles all the web scraping infrastructure. Pre-built Instagram Actors give me structured data that I pipe directly into my AI scoring pipeline. The REST API integration with my Node.js/Express backend was seamless — well-documented endpoints, predictable response formats, and solid error handling. Review collected by and hosted on G2.com.

The learning curve for building custom Actors is steeper than I expected. Also, some third-party Actors in the marketplace vary in quality — it would help to have more standardized output schemas across similar Actors. Review collected by and hosted on G2.com.

The MCP gave me the ability to build and deploy 7 actors collecting 250,000+ rows of marketplace data in 6 weeks — by talking to Claude. The core primitives (call-actor, get-actor-run, get-actor-output) are the right shape for agentic workflows. search-actors and fetch-actor-details let me discover existing actors instead of reinventing the wheel. And search-apify-docs is underrated — having Claude pull up the right docs without context-switching to a browser is a small thing that compounds.

The bigger insight: Apify composes well with other MCPs. In my workflow it's Apify (collect) + Supabase (store) + Claude (orchestrate). Each does one thing; the conversation stitches them together. That multi-MCP pattern is where I think the real value is. Review collected by and hosted on G2.com.

The default Claude desktop / Cowork connector ships with a fairly limited tool set. The core operational tools (run history, abort, logs, schedule listing) do exist, but they’re tucked away in a separate MCP Configurator—and I didn’t even know the configurator existed until a PM personally walked me through it. Up to that point, I assumed those capabilities were missing entirely and ended up falling back to REST API workarounds.

This feels more like a discoverability problem than an actual product gap, but it still cost real time. Either ship the operations tools enabled by default, or make the configurator clearly visible during connector setup so it’s obvious where those features live. Review collected by and hosted on G2.com.

What I like best about Apify is how intuitive and reliable the platform is, even for someone who isn’t a developer. It turns complex web automation into a simple, repeatable workflow that saves me hours every week. The combination of ready‑to‑use Actors, clear documentation, and seamless integrations makes it incredibly easy to build and scale automations without worrying about infrastructure. I also appreciate how stable the runs are and how consistent the data output is — it gives me confidence that my processes will work the same way every time. Overall, Apify removes friction instead of creating it, which makes it one of the most efficient tools in my workflow. Review collected by and hosted on G2.com.

There isn’t much I genuinely dislike about Apify, but there are a few areas where the experience could be even smoother. Debugging can sometimes feel a bit unclear, especially when different errors look similar and require extra time to interpret. The versioning workflow in the Web IDE could also be more intuitive, as it’s not always obvious which build is currently active. These aren’t major downsides, but small improvements here would make an already excellent platform even more seamless to use. Review collected by and hosted on G2.com.

It handles the scraping targets that would otherwise be impossible for a small team - Facebook, Instagram, and Cloudflare-protected sites like Resident Advisor. Instead of fighting constant UI changes and bot protection, we plug in a managed actor, get clean JSON, and focus on the actually differentiated parts of our product (AI extraction, search UX). The pay-per-use pricing and ready-to-run actor store make it viable even for a small side project. Review collected by and hosted on G2.com.

Actor discovery is the weakest part. Searching for something like "facebook events" returns a dozen overlapping actors with no clear signal on which is officially maintained, actively updated, or reliable in production. Trust badges, last-updated dates, and a recommended output schema per platform would save a lot of trial-and-error evaluation time. Cost predictability for long crawler runs could also be better - a dry-run estimator would help. Review collected by and hosted on G2.com.

What I appreciate the most is the incredible time-saving offered by the Store. Having access to hundreds of pre-configured "Actors" for the most popular sites allows projects to be launched in just a few clicks. Moreover, their intelligent management of proxies and cloud infrastructure is remarkably reliable, allowing focus on data analysis rather than technical maintenance. Review collected by and hosted on G2.com.

Honestly, the only negative point is that I wish I could use it even more intensively! Unfortunately, my budget is not unlimited, and since the tool is extremely efficient, one quickly wants to extend it to all our projects. An even more flexible pricing structure for small businesses or intermediate projects would be the icing on the cake. Review collected by and hosted on G2.com.

What I like most about Apify is how it combines powerful web scraping capabilities with an easy-to-use cloud platform. The large library of ready-to-use actors saves a lot of development time, while scheduling, APIs, datasets, and integrations make it simple to build reliable automation workflows. I also appreciate that I don't have to manage infrastructure, allowing me to focus on solving business problems instead of maintaining scraping systems. Review collected by and hosted on G2.com.

The biggest downside is that credit usage can be difficult to predict for larger or more complex scraping jobs, making it harder to estimate costs in advance. The interface also has a learning curve because many features are spread across different sections. Finally, while the Actor Store is a major strength, the quality and maintenance of community actors can vary, so it sometimes takes time to find the most reliable option for a specific use case. Review collected by and hosted on G2.com.

What I like most is how easy it is to automate repetitive web data collection. The large library of Actors, reliable infrastructure, and straightforward API make it simple to build workflows without spending time managing scraping infrastructure. It saves time and scales well. Review collected by and hosted on G2.com.

The learning curve can be a bit steep when working with more advanced workflows, especially for new users. However, the documentation and community resources make it much easier to get up to speed. Review collected by and hosted on G2.com.