Top 7 Firecrawl Alternatives Compared: Pricing and Features

If you're building AI agents, RAG pipelines, or data workflows that depend on live web data, you've probably considered Firecrawl. It's a solid tool — but at $83/month for the Standard plan (100K credits), the pricing scales hard. Developers building side projects or cost-sensitive production systems need to know what else is out there.

This breakdown covers 7 Firecrawl alternatives with real pricing, feature comparisons, and code examples. Whether you need cheaper per-page costs, better structured data extraction, or a combined search-plus-scrape API, there's an option here.

Key Takeaways

• Firecrawl starts at free (500 credits) but jumps to $16/month for 3K credits and $83/month for 100K — steep for small teams
• SearchHive offers search, scraping, and deep research in one API starting at $9/month for 5K credits — the cheapest combined option
• Tavily is search-only ($0.008/credit) — great for AI agents that don't need raw HTML
• Exa specializes in semantic search ($7/1K requests) — built for code retrieval and knowledge-intensive agents
• Apify uses compute units ($0.20-$0.30/CU) — powerful for complex scraping but pricing is unpredictable
• ScrapingBee is developer-focused ($49/month for 150K credits) — reliable for high-volume single-page scraping
• Jina AI Reader is free for basic use — good for Markdown conversion of URLs, not a full scraping platform

1. SearchHive — Search + Scrape + Research, One API

SearchHive combines SwiftSearch (search engine API), ScrapeForge (web scraping), and DeepDive (deep research) into a single platform. No juggling multiple subscriptions.

Pricing: Free (500 credits) → Starter $9/month (5K) → Builder $49/month (100K) → Unicorn $199/month (500K)

At 100K credits, SearchHive's Builder plan costs $49/month compared to Firecrawl's $83/month for the same volume. The 41% savings compounds at scale — the Unicorn plan gives you 500K credits for $199 versus Firecrawl's $333/month for the Growth plan.

import requests

API_KEY = "your_searchhive_key"
BASE = "https://api.searchhive.dev/v1"

# Scrape a page with ScrapeForge
resp = requests.get(f"{BASE}/scrape", params={
    "api_key": API_KEY,
    "url": "https://example.com/product-page",
    "format": "markdown",
    "extract": "price,title,description,availability"
})
data = resp.json()
print(data["content"])  # Clean markdown with extracted fields

# Search with SwiftSearch
search = requests.get(f"{BASE}/search", params={
    "api_key": API_KEY,
    "query": "best web scraping APIs 2026",
    "num_results": 10
})
for result in search.json()["results"]:
    print(result["title"], result["url"])

The advantage over Firecrawl is the unified API. Firecrawl handles scraping well but has no native search engine API — you'd need a separate SerpApi or Tavily subscription for that.

2. Tavily — AI-Native Search API

Tavily is built specifically for AI agents. It returns search results optimized for LLM consumption — clean text, relevance scores, and no SEO noise.

Pricing: Free (1K credits/month) → Pay-as-you-go ($0.008/credit) → Enterprise (custom)

At scale, 100K Tavily searches costs $800/month. That's 10x more expensive than SearchHive's $49/100K for search alone — but Tavily's results are pre-filtered for AI relevance, which can save token costs downstream.

import requests

response = requests.post("https://api.tavily.com/search", json={
    "api_key": "your_tavily_key",
    "query": "Python web scraping libraries comparison",
    "max_results": 5,
    "include_answer": True
})

data = response.json()
print(data["answer"])  # Direct answer string
for r in data["results"]:
    print(f"- {r['title']}: {r['url']}")

Tavily has no scraping endpoint. If you need raw page content, you pair it with something else — which means two APIs, two bills, two integration points.

3. Exa — Semantic Web Search

Exa (formerly Metaphor) uses neural search instead of keyword matching. You describe what you want in natural language, and it finds semantically relevant pages.

Pricing: Free (1K requests) → Search $7/1K → Deep Search $12/1K → Contents $1/1K pages

Exa excels at finding specific types of content — documentation, code repositories, research papers. Its coding agent use case is particularly strong (Cursor uses Exa for docs retrieval).

import requests

response = requests.post("https://api.exa.ai/search", headers={
    "x-api-key": "your_exa_key"
}, json={
    "query": "web scraping API documentation with rate limits",
    "num_results": 10,
    "type": "auto",
    "contents": {"text": {"maxCharacters": 1000}}
})

for result in response.json()["results"]:
    print(f"{result['title']} (score: {result['score']})")
    print(result["text"][:200])

The limitation: Exa is search-only, no scraping. And at $7/1K for basic search, it's more expensive than SearchHive's all-in pricing.

4. Apify — Actor-Based Scraping Platform

Apify takes a different approach. Instead of a simple API, you run "Actors" — pre-built or custom scraping programs on their infrastructure. It's powerful but complex.

Pricing: Free ($5 usage) → Starter $29/month → Scale $199/month → Business $999/month. Plus $0.20-$0.30 per compute unit beyond your plan.

The $199/month Scale plan gives $199 in store credit plus discounted compute units at $0.25/CU. A typical scrape job might use 0.1-1 CU depending on complexity — so actual costs are hard to predict upfront.

from apify_client import ApifyClient

client = ApifyClient("your_apify_token")

# Run a pre-built Actor
run = client.actor("apify/web-scraper").call(run_input={
    "startUrls": [{"url": "https://example.com/products"}],
    "pageFunction": 'async function pageFunction(context) { const { request, $ } = context; const title = $("h1").text(); const price = $(".price").text(); return { url: request.url, title, price }; }',
    "maxPages": 100
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Apify is overkill if you just need to scrape pages via API. But for complex workflows (login sequences, pagination, JavaScript rendering), it's the most capable platform here.

5. ScrapingBee — Developer-First Scraping API

ScrapingBee focuses on one thing: making web scraping simple and reliable. It handles proxies, headless browsers, and CAPTCHAs automatically.

Pricing: Freelancer $49/month (150K credits) → Startup $99/month (500K) → Business $249/month (2M)

At $49/month for 150K credits, ScrapingBee is competitively priced for pure scraping. The per-page cost works out to ~$0.33/1K pages — cheaper than Firecrawl's Standard plan.

import requests

response = requests.get("https://app.scrapingbee.com/api/v1/", params={
    "api_key": "your_scrapingbee_key",
    "url": "https://example.com",
    "render_js": True,
    "extract_rules": '{"title": "h1", "price": ".price"}'
})

print(response.text)

No search API, no deep research. Pure scraping — and it does it well. But you'll need another tool for search or content discovery.

6. Jina AI Reader — Free Markdown Extraction

Jina AI Reader converts any URL to clean Markdown. It's not a full scraping platform — more of a utility for getting readable content from the web.

Pricing: Free for basic use → $3/1K pages for higher limits → Enterprise available

import requests

# Simple GET-based conversion — no API key needed for basic use
markdown = requests.get(
    "https://r.jina.ai/https://example.com/long-article",
    headers={"Accept": "text/markdown"}
).text

print(markdown[:500])

Extremely simple, extremely limited. No structured extraction, no search, no batch processing. Useful as a complement to other tools but not a Firecrawl replacement on its own.

7. SerpApi — Search Engine Results API

SerpApi is the most established SERP API — it parses Google, Bing, YouTube, and other search engine results into structured free JSON formatter.

Pricing: Free (250 searches) → Starter $25/month (1K) → Developer $75/month (5K) → Production $150/month (15K)

SerpApi gets expensive fast. At $75/month for 5K searches, you're paying $15/1K — compared to SearchHive's SwiftSearch which effectively charges ~$1.80/1K searches at the Builder tier.

from serpapi import GoogleSearch

search = GoogleSearch({
    "api_key": "your_serpapi_key",
    "q": "best web scraping APIs 2026",
    "num": 10,
    "location": "Austin, Texas"
})

results = search.get_dict()
for r in results.get("organic_results", []):
    print(f"{r['position']}. {r['title']} - {r['link']}")

Excellent data quality for search results, but no scraping capability. And the pricing doesn't scale — 100K searches costs $725/month.

Comparison Table

The Verdict

If you need only web scraping, Firecrawl is solid but ScrapingBee offers better per-page pricing at volume. If you need only search, Tavily and Exa have better AI-optimized results than Firecrawl's basic Map endpoint.

If you need both search and scraping — which most AI agent and RAG workflows do — Firecrawl forces you to accept limited search or bolt on a second API. SearchHive bundles search, scraping, and deep research into a single credit system at 41% lower cost for equivalent volumes.

Start with the free tier (500 credits, no card required) and see how far one API gets you before considering a multi-tool stack.