Firecrawl turns a URL into clean markdown. One API call, structured output, LLM-ready. For static extraction, it's one of the best tools available — 103K GitHub stars, Y Combinator backed, and a developer community that ships fast.

But then your workflow needs to log into a site. Or click through a filter dropdown before the data appears. Or navigate three pages deep into an authenticated dashboard. Firecrawl hands you the page. TinyFish hands you the workflow.

This isn't a question of which tool is "better." It's a question of where each one stops and the other starts.

Firecrawl is a web scraping API that converts URLs into clean markdown or structured JSON for LLM pipelines. TinyFish is a web agent platform that runs AI agents on remote browsers to complete multi-step workflows and return structured data.

Quick Reference: Which Tool Fits Your Situation?

1. You need clean markdown from public pages at scale → Firecrawl
2. You need to navigate, interact, then extract → TinyFish
3. You need full-site crawl and URL discovery → Firecrawl
4. You need authenticated multi-step workflows → TinyFish
5. You want to self-host your scraping infrastructure → Firecrawl
6. You want all infrastructure bundled in one step-based price → TinyFish
7. You're looking for a Firecrawl alternative for interactive workflows → TinyFish
8. You're looking for a TinyFish alternative for bulk extraction → Firecrawl

What Each Product Actually Does

Firecrawl is a web scraping and crawling API. It converts raw web pages into clean markdown or structured JSON — formats designed for LLM consumption, RAG pipelines, and AI agent workflows. The product surface is broad:

• /scrape — extract a single page
• /crawl — recursively discover and scrape an entire domain
• /map — return all URLs on a site in seconds
• /extract — LLM-powered structured data extraction with Pydantic schemas
• /agent — autonomous browsing from a natural language prompt (powered by FIRE-1)
• /interact — scrape a page, then take actions on it

Firecrawl is open source (AGPL-3.0 core, Fire-Engine proprietary), self-hostable, and integrates natively with LangChain, LlamaIndex, n8n, Zapier, and MCP. Over 500K developers and 80K+ companies use it. Customers include Shopify, Zapier, Canva, and Apple.

TinyFish is a web agent platform. You describe a task in plain English, and TinyFish runs a full browser session — navigating, interacting, authenticating, and extracting — then returns structured JSON.

curl -N -X POST https://agent.tinyfish.ai/v1/automation/run-sse \
  -H "X-API-Key: $TINYFISH_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://example.com",
    "goal": "Log in with credentials, navigate to the pricing dashboard, extract all plan names and prices as JSON"
  }'

One endpoint. One API key. Browser, proxy, LLM inference, and anti-bot protection all included. Customers include Google, DoorDash, and ClassPass.

The architecture difference matters: Firecrawl gives you specialized tools for each job. TinyFish gives you one tool that figures out the job.

Where Firecrawl Wins

Give credit where it's due.

Full-site crawling. Firecrawl's /crawl endpoint recursively discovers and extracts content across an entire domain. The /map endpoint returns every URL on a site in seconds. If you're building a RAG pipeline that needs to ingest an entire documentation site or knowledge base, this is purpose-built for the job. TinyFish can navigate multiple pages via its agent, but it doesn't have a dedicated crawl endpoint — it's designed for targeted workflows, not bulk content ingestion.

Open source and self-hostable. The core is AGPL-3.0. If your organization requires code inspection, self-deployment, or data residency, Firecrawl gives you that option. TinyFish is a managed service — you can't run it on your own infrastructure (outside of Enterprise on-premise options).

Ecosystem breadth. Native integrations with LangChain, LlamaIndex, Zapier, Make, n8n, and a growing list of AI frameworks. 103K GitHub stars means a large community building extensions, writing tutorials, and reporting bugs. For developer adoption, this ecosystem is hard to beat.

Pydantic schema extraction. The /extract endpoint lets you define exact data schemas using Pydantic, and Firecrawl's LLM fills them in. For teams that need predictable, typed output structures from static pages, this is cleaner than free-form goal descriptions.

Where the Gap Opens

Firecrawl's strengths are in content extraction — getting data off pages that are already accessible. The gap appears when the data isn't just sitting there waiting to be scraped.

Authentication. Firecrawl's /agent and browser sandbox can handle some login flows, but the core /scrape and /crawl endpoints don't manage session state across authenticated pages. If your workflow requires logging in, navigating a dashboard, and extracting data from a protected page, you're assembling that logic yourself. TinyFish treats authentication as part of the task — describe the login in your goal, and the agent handles credentials, session state, and navigation as a single workflow.

Multi-step interaction. The new /interact endpoint lets you scrape a page and then take actions on it — a step forward. But for workflows that span multiple pages with conditional logic (if this dropdown shows X, click it; if not, try Y), you're chaining API calls and managing state between them. TinyFish handles the full sequence in one call because the agent reasons about each step.

Anti-bot protection. Independent testing — including a head-to-head comparison by Scrape.do that found Firecrawl succeeded on only 1 of 6 protected sites — has shown lower success rates for Firecrawl on sites with serious anti-bot measures. TinyFish runs every request through a native stealth layer with automatic anti-bot handling and residential proxy rotation — no extra configuration needed beyond browser_profile: "stealth". The infrastructure handles Cloudflare, PerimeterX, and most common protection systems. (TinyFish does have limitations on DataDome and hCaptcha — see our anti-bot protection guide for honest details.)

Geographic routing. TinyFish supports geographic proxy routing (US, GB, CA, DE, FR, JP, AU) with a single parameter. Sites that serve different content based on location — pricing pages, regional catalogs, geo-restricted content — are handled natively.

Pricing: Credits vs Steps

The pricing models look similar on the surface — both are usage-based — but the mechanics are different.

Firecrawl: Credits with multipliers

Firecrawl charges 1 credit per page for basic scraping. But feature multipliers stack:

• JSON extraction: +4 credits per page
• Enhanced mode: +4 credits per page
• Crawl + extract combo: 7 credits per page

A team on the Standard plan (100,000 credits/month at $83/mo) running JSON + Enhanced Mode burns 9 credits per page — giving them roughly 11,100 pages, not 100,000. The /extract endpoint has separate token billing starting at $89/mo. Credits don't roll over.

The self-hosted option avoids the subscription but shifts infrastructure costs to your team — proxy management, scaling, security patches, and updates.

TinyFish: Steps, all-inclusive

TinyFish charges per step. One step = one action on a live website. Everything is included: browser, proxy, LLM inference, anti-bot. No multipliers, no separate line items.

Step count varies by task complexity. A simple data extraction might take 3–5 steps. A full login-navigate-extract workflow might take 15–20 steps. Workflows never hard-stop mid-execution if you exceed your included steps — they continue at the overage rate.

The real cost comparison

For a fair comparison, consider a workflow that extracts product prices from 100 pages:

If the pages are static and public: Firecrawl wins on cost. 100 credits on any plan, possibly less than a dollar. TinyFish would use 3–5 steps per page (300–500 steps), costing $4.50–$7.50 on PAYG.

If the pages require login and navigation: Firecrawl requires you to build the authentication and navigation logic — your engineering time is the real cost. TinyFish handles it in one API call at $0.015/step. The step cost is higher per action, but the total project cost (including your time) is often lower.

The decision isn't just per-unit price. It's per-unit price plus the engineering hours you don't spend building orchestration.

When to Use Both

Here's the thing: these tools solve different problems, and many teams will use both.

Firecrawl for bulk content ingestion. Crawl your competitor's blog, ingest documentation sites, build RAG knowledge bases from public web content. Firecrawl does this faster and cheaper than any agent-based approach.

TinyFish for the workflows that require interaction. Monitor prices behind login walls. Extract data from dashboards. Complete multi-step form submissions. Run parallel authenticated sessions across hundreds of sites.

They coexist naturally. Use Firecrawl to discover and extract what's publicly available. Use TinyFish for everything that requires a browser session, authentication, or multi-step logic.

Decision Framework

Try It on a Real Workflow

The best way to evaluate is to test both on your actual use case. If your workflow is static extraction, Firecrawl's free tier (500 lifetime credits) will tell you fast.

If your workflow involves login, navigation, or interaction — the kind of thing that breaks traditional scrapers — try it on TinyFish. 500 free steps, no credit card. Test your actual target site and get structured results in under 10 minutes.

👉 Start free on TinyFish

FAQ

What about Firecrawl's new /agent endpoint?

Firecrawl's /agent endpoint (powered by their FIRE-1 model) is a meaningful addition. It accepts a natural language prompt, browses autonomously, and returns structured JSON with citations. For simple agent tasks — "find pricing on this page and return it as JSON" — it works and is competitively priced within Firecrawl's credit system.

Where the differences emerge is in scope and track record. TinyFish's agent runs on a full remote browser session with built-in stealth, residential proxies, and session persistence across multi-step flows. It scored 90% on the Mind2Web benchmark across 136 live websites — all 300 tasks run in parallel, every execution trace published publicly. Firecrawl's /agent doesn't have a comparable public benchmark yet, and FIRE-1 agent requests are billed even on failure (per Firecrawl's billing docs), which adds cost unpredictability for complex tasks.

For simple, single-page agent tasks, both tools can handle the job. For multi-step authenticated workflows where reliability at scale matters, TinyFish's agent infrastructure has a deeper production track record. As Firecrawl's /agent matures, this gap may narrow — worth re-evaluating as both products ship updates.

How does pricing compare for a typical use case?

For 10,000 pages of static content extraction, Firecrawl's Standard plan ($83/mo, 100K credits) is significantly cheaper. For 100 authenticated workflows that each require login + navigation + extraction, TinyFish's step-based pricing ($0.015/step, all infra included) is more economical when you factor in the engineering time you'd spend building authentication logic for Firecrawl. The right comparison depends on your specific workflow.

Can I use Firecrawl and TinyFish together?

Yes, and many teams do. A common pattern: Firecrawl discovers and extracts content from public pages (via /crawl and /scrape), while TinyFish handles the authenticated or interactive workflows that require a full browser session. They serve different parts of the same pipeline.

How does anti-bot handling compare?

Firecrawl handles basic anti-bot scenarios through its rendering engine. Independent tests have shown mixed results on heavily protected sites. TinyFish includes a native stealth layer with residential proxy rotation and automatic anti-bot handling on every request — no extra configuration or cost. Both tools have limitations on the most aggressive protection systems.

Which tool is better for RAG pipelines?

For ingesting large volumes of public web content into a RAG system, Firecrawl is purpose-built. Its markdown output is optimized for token efficiency, and the /crawl endpoint handles full-site ingestion. If your RAG pipeline needs data from authenticated sources or dynamic pages that require interaction, TinyFish fills that gap.

Is Firecrawl open source?

Yes. Firecrawl's core is AGPL-3.0 and self-hostable. The Fire-Engine (responsible for browser rendering and anti-bot handling) is proprietary. TinyFish is a managed service with partial open source components (AgentQL). If code inspection or self-deployment is a requirement, Firecrawl has the advantage here.

Related Reading

• Why AI Agents Need a Unified Web Infrastructure
• TinyFish vs Browserbase: Cold Start, Pricing, and Real-World Performance
• How TinyFish Handles Anti-Bot Protection