TinyFish AI Web Agents

What do you like best about the product?

a simple and easy-to-understand platform

What do you dislike about the product?

too many tabs, sometimes it's difficult to find your way

What problems is the product solving and how is that benefiting you?

yes, it's very effective

What do you like best about the product?

How easy it is to use. You can set up new profiles so you can have whatever AI you are working with better help navigate the user experience

What do you dislike about the product?

So far not too much. The concept that brought me here is basically free but that makes me want to do business with these guys. I want to do the same with my project CoinFox or something similar

What problems is the product solving and how is that benefiting you?

Being able to have whatever AI I'm using get on whatever account I need it to

What do you like best about the product?

Smooth onboarding, it takes no longer than 30 s to get started

What do you dislike about the product?

Its free web search is a game changer I guess

What problems is the product solving and how is that benefiting you?

Web search

What do you like best about the product?

super easy to use, integrates well with Claude. Good to see my balance & wallet easily Thanks for the discount. I'd like another 30% discount promo code, please, for the future - I am working as a volunteer, hence these are my private costs

What do you dislike about the product?

thankfully nothing yet, it's going well.

What problems is the product solving and how is that benefiting you?

Scraping a website with many job offers for young people finishing school. 1yrs back, no AI was able to do so. In August, Claude was able to do so. But then the website owners must have found out and stopped Claude. But TinyFish it THE solution at a fair price, as I am volunteer and have to pay on my own.

What do you like best about the product?

The Search and Fetch APIs give coding agents live web access without me running Playwright or a proxy stack. Fetch renders JS-heavy docs and returns clean Markdown, which cuts token waste and beats a raw HTML dump. One API key for search, fetch, browser and agent is simpler than stitching three vendors. The free Search + Fetch tier is enough for daily agent work.

What do you dislike about the product?

Fetch can take several seconds on heavy SPA pages, and Search is not always fresh on events from the last few hours. Agent and Browser credits climb quickly once you leave read-only fetch and start multi-step automation. Sessions do not share state well, so parent-child or parallel campaign flows need extra orchestration on my side. Docs on advanced error handling could be clearer.

What problems is the product solving and how is that benefiting you?

Coding agents still hit a wall on the live web: stale search, empty SPA shells, and no clean way to read current docs without standing up Playwright, proxies and anti-bot handling. TinyFish replaces that stack with Search + Fetch under one API key. Agents get rendered pages as Markdown instead of raw HTML, so answers stay current and token use drops. I spend less time babysitting browsers and more time on the actual task. Browser/Agent is there if a flow needs login or clicks, without me running a cloud browser fleet.

What do you like best about the product?

best i have use more then four or five automation tool but it was fantastic

What do you dislike about the product?

in this tool like minmum tookens so very quckly end the tookens

What problems is the product solving and how is that benefiting you?

provide more credits or a fast and deep verfiy

What do you like best about the product?

Tinyfish provides exclusive AI agents that can actually surf websites and return structured outputs. They support different trigger modes, including API-triggered and headless modes, as well as geo-specific mode. There is also a silent crawling mode.

These are goal-oriented agents, not just tools. Each search session is available and integratable via streamable APIs, and every session includes logs that can be pulled through separate APIs. If Tinyfish is used within other websites, we can be reassured that we don’t need to host LLMs or build and maintain a system for managing search sessions, history, and related details—Tinyfish takes care of all of that. Parallel sessions are also possible, which helps improve the speed of research. The UI has the sessions, it holds profiles and is sleek. The pricing is optimal. The communities are well present and active for any help and getting started is really easy.

What do you dislike about the product?

Tinyfish web sessions or instances are independent and do not share information with each other. So, if we need a parent-child relationship between browser sessions and want certain parts of a campaign to run in parallel mode, it becomes difficult. For example, if we want agents to trigger multiple parallel sub-sessions, each with its own browser, while still sharing the data collected across those browsers, that kind of feature is not available.

What problems is the product solving and how is that benefiting you?

Tinyfish solves the problem of web-related research agent. so in case we need a campaign-like feature in our application we can easily just integrate this rather than building a system to maintain and scale web agents. This also solves the step-by-step exploration of websites and automation testing. Here we do not need to have automation scripts made and maintained every time, since Tinyfish dynamically works with the websites, it can do testing with just natural language instructions as input and generate reports in any asked format.

What do you like best about the product?

What I like most about TinyFish is how it lets AI agents interact with real websites and complete tasks through the browser instead of being limited to APIs or static data. This makes it especially useful for automating workflows that would normally require manually navigating websites, extracting information, and taking actions across different web services.

The biggest value for me is the combination of AI intelligence and browser automation. It allows me to turn a natural-language goal into an actionable workflow, which can significantly reduce repetitive work. I also like the potential for integrations because the same approach can be applied across websites without needing to build a custom integration for every individual service.

The overall experience makes TinyFish feel less like a simple scraping tool and more like infrastructure for building practical AI agents that can actually operate on the web. On a daily basis, TinyFish is incredibly smooth to integrate into our automated pipelines. The interface—whether using their REST API, TypeScript SDK, or CLI—is intuitive and cuts out the huge headache of managing browser servers, proxies, and anti-bot bypass mechanisms manually. The sub-250ms cold starts mean our agents execute web actions instantly without hanging. It provides a seamless, developer-friendly experience that removes the clunkiness of old web scraping stacks.

What do you dislike about the product?

The main area I think TinyFish could improve is the learning curve around building and debugging more complex browser-agent workflows. The basic concept is powerful, but when an agent encounters an unexpected website state or a workflow fails midway, it would be helpful to have even more detailed debugging information and clearer visibility into exactly what the agent attempted.

I’d also like to see broader integrations, more examples for advanced use cases, and clearer guidance around performance and pricing as workflows scale. These improvements would make it easier to move from experimenting with TinyFish to confidently using it in production.

What problems is the product solving and how is that benefiting you?

TinyFish solves the problem of automating web-based tasks that would normally require manually navigating websites or building separate integrations for every service. Instead of relying entirely on APIs, I can use AI agents to interact with real websites, retrieve information, and carry out multi-step workflows.

This benefits me because I work on AI and automation projects where connecting different web services can otherwise take significant development time. TinyFish reduces the amount of repetitive browser work and makes it easier to prototype practical AI agents that can operate on the web.

It also opens up use cases that would be difficult to automate through traditional APIs alone, allowing me to focus more on the product logic and user experience rather than maintaining custom integrations for every website.

What do you like best about the product?

TinyFish is the page-scrape layer I actually trust after a search API. I run Tavily for broad hits, then TinyFish run-sse against a specific URL with a goal — Gensyn docs, DoraHacks briefs, GitHub orgs, hackathon portals — and it returns extractable text instead of “10 blue links.” Header is just X-API-Key. That one-call shape is easy to drop into a Node agent: POST { url, goal }, parse SSE data: lines, keep the COMPLETE payload. On my research desk I credit-gate it (max per cycle/hour) so I don’t burn the key, and I only fire it when a question cites a primary URL. That’s the upside: it closes the loop from “I found a page” to “I have the words on that page,” which is what stops me inventing deadlines and prize amounts. The automated piece I use is the web agent over SSE, not a chat UI. I POST a live URL plus a goal (extract get-started network names, pull prize/deadline text, summarize this GitHub org page) and parse data: events until COMPLETE. That is what sits in my TypeScript desk: credit-gated, max per cycle/hour, only when a question already cites a primary URL. The AI is useful when the goal is tight and the page is official. It is weaker when the goal is fuzzy or the page is a listing dump — you still have to read the extract and mark thin results unverified. I do not let it auto-trade or auto-publish off the scrape.

What do you dislike about the product?

It isn’t magic on hostile pages. Cloudflare-gated UIs and noisy listing pages (I burned a pass on a Reddit listing that came back generic/unrelated) still fail or waste a credit. I treat a thin extract as unverified, not as a fact. Credits mean you have to budget it; I wouldn’t fire TinyFish on every search hit.

What problems is the product solving and how is that benefiting you?

Builder/research agents that must quote primary sources. AFTERCUT and my scout stack: official docs, hackathon pages, GitHub. TinyFish is the “open this URL and pull the text” step. Search alone is not enough for that.

What do you like best about the product?

The Fetch API has been a game-changer for us. It quickly turns messy HTML into clean, LLM-ready Markdown, which has significantly reduced our token costs and improved AI accuracy. On top of that, the generous free tier for Search and Fetch makes it a low-risk, high-value addition to our stack. TinyFish integrates seamlessly with my stack. The native MCP support makes connecting to Claude Code and Cursor pretty easy.

What do you dislike about the product?

The Agent feature’s accuracy still feels like it’s maturing. On complex, dynamic pages it occasionally hallucinates data, which means I can’t fully trust it to run autonomously on production-critical tasks without manual validation. Also, the daily OAuth expiration for MCP usage is frustrating and disrupts workflow continuity.

What problems is the product solving and how is that benefiting you?

TinyFish addresses the issue of stale training data and noisy web pages. By delivering clean, up-to-date Markdown through Fetch, my AI models can pull in current, accurate information without having to sift through ads, pop-ups, or navigation bars. As a result, answer quality has improved and token usage is noticeably lower, which helps keep our application fast and reliable.