Firecrawl scraper
ClaudeSkillz: For when you need skills, but lazier
npx -y skills add jackspace/ClaudeSkillz --skill firecrawl-scraperAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 15 stars15 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data. Use when: scraping websites, crawling entire sites, extracting web content, converting HTML to markdown, building web scrapers, handling dynamic JavaScript content, bypassing anti-bot protection, extracting structured data from web pages, or when encountering "content not loading", "JavaScript rendering issues", or "blocked by bot detection". Keywords: firecrawl, firecrawl api, web scraping, web crawler, scrape website, crawl website, extract content, html to markdown, site crawler, content extraction, web automation, firecrawl-py, firecrawl-js, llm ready data, structured data extraction, bot bypass, javascript rendering, scraping api, crawling api, map urls, batch scraping
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
16.1 KB, as published. Nobody here has run it
Firecrawl Web Scraper Skill
Status: Production Ready ✅ Last Updated: 2025-10-24 Official Docs: https://docs.firecrawl.dev API Version: v2
What is Firecrawl?
Firecrawl is a Web Data API for AI that turns entire websites into LLM-ready markdown or structured data. It handles:
- JavaScript rendering - Executes client-side JavaScript to capture dynamic content
- Anti-bot bypass - Gets past CAPTCHA and bot detection systems
- Format conversion - Outputs as markdown, JSON, or structured data
- Screenshot capture - Saves visual representations of pages
- Browser automation - Full headless browser capabilities
API Endpoints
1. /v2/scrape - Single Page Scraping
Scrapes a single webpage and returns clean, structured content.
Use Cases:
- Extract article content
- Get product details
- Scrape specific pages
- Convert HTML to markdown
Key Options:
formats: ["markdown", "html", "screenshot"]onlyMainContent: true/false (removes nav, footer, ads)waitFor: milliseconds to wait before scrapingactions: browser automation actions (click, scroll, etc.)
2. /v2/crawl - Full Site Crawling
Crawls all accessible pages from a starting URL.
Use Cases:
- Index entire documentation sites
- Archive website content
- Build knowledge bases
- Scrape multi-page content
Key Options:
limit: max pages to crawlmaxDepth: how many links deep to followallowedDomains: restrict to specific domainsexcludePaths: skip certain URL patterns
3. /v2/map - URL Discovery
Maps all URLs on a website without scraping content.
Use Cases:
- Find sitemap
- Discover all pages
- Plan crawling strategy
- Audit website structure
4. /v2/extract - Structured Data Extraction
Uses AI to extract specific data fields from pages.
Use Cases:
- Extract product prices and names
- Parse contact information
- Build structured datasets
- Custom data schemas
Key Options:
schema: Zod or JSON schema defining desired structuresystemPrompt: guide AI extraction behavior
Authentication
Firecrawl requires an API key for all requests.
Get API Key
- Sign up at https://www.firecrawl.dev
- Go to dashboard → API Keys
- Copy your API key (starts with
fc-)
Store Securely
NEVER hardcode API keys in code!
# .env file
FIRECRAWL_API_KEY=fc-your-api-key-here
# .env.local (for local development)
FIRECRAWL_API_KEY=fc-your-api-key-here
Python SDK Usage
Installation
pip install firecrawl-py
Latest Version: firecrawl-py v4.5.0+
Basic Scrape
import os
from firecrawl import FirecrawlApp
# Initialize client
app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))
# Scrape a single page
result = app.scrape_url(
url="https://example.com/article",
params={
"formats": ["markdown", "html"],
"onlyMainContent": True
}
)
# Access markdown content
markdown = result.get("markdown")
print(markdown)
Crawl Multiple Pages
import os
from firecrawl import FirecrawlApp
app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))
# Start crawl
crawl_result = app.crawl_url(
url="https://docs.example.com",
params={
"limit": 100,
"scrapeOptions": {
"formats": ["markdown"]
}
},
poll_interval=5 # Check status every 5 seconds
)
# Process results
for page in crawl_result.get("data", []):
url = page.get("url")
markdown = page.get("markdown")
print(f"Scraped: {url}")
Extract Structured Data
import os
from firecrawl import FirecrawlApp
app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))
# Define schema
schema = {
"type": "object",
"properties": {
"company_name": {"type": "string"},
"product_price": {"type": "number"},
"availability": {"type": "string"}
},
"required": ["company_name", "product_price"]
}
# Extract data
result = app.extract(
urls=["https://example.com/product"],
params={
"schema": schema,
"systemPrompt": "Extract product information from the page"
}
)
print(result)
TypeScript/Node.js SDK Usage
Installation
npm install @mendable/firecrawl-js
# or
pnpm add @mendable/firecrawl-js
# or use the unscoped package:
npm install firecrawl
Latest Version: @mendable/firecrawl-js v4.4.1+ (or firecrawl v4.4.1+)
Basic Scrape
import FirecrawlApp from '@mendable/firecrawl-js';
// Initialize client
const app = new FirecrawlApp({
apiKey: process.env.FIRECRAWL_API_KEY
});
// Scrape a single page
const result = await app.scrapeUrl('https://example.com/article', {
formats: ['markdown', 'html'],
onlyMainContent: true
});
// Access markdown content
const markdown = result.markdown;
console.log(markdown);
Crawl Multiple Pages
import FirecrawlApp from '@mendable/firecrawl-js';
const app = new FirecrawlApp({
apiKey: process.env.FIRECRAWL_API_KEY
});
// Start crawl
const crawlResult = await app.crawlUrl('https://docs.example.com', {
limit: 100,
scrapeOptions: {
formats: ['markdown']
}
});
// Process results
for (const page of crawlResult.data) {
console.log(`Scraped: ${page.url}`);
console.log(page.markdown);
}
Extract Structured Data with Zod
import FirecrawlApp from '@mendable/firecrawl-js';
import { z } from 'zod';
const app = new FirecrawlApp({
apiKey: process.env.FIRECRAWL_API_KEY
});
// Define schema with Zod
const schema = z.object({
company_name: z.string(),
product_price: z.number(),
availability: z.string()
});
// Extract data
const result = await app.extract({
urls: ['https://example.com/product'],
schema: schema,
systemPrompt: 'Extract product information from the page'
});
console.log(result);
Common Use Cases
1. Documentation Scraping
Scenario: Convert entire documentation site to markdown for RAG/chatbot
app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))
docs = app.crawl_url(
url="https://docs.myapi.com",
params={
"limit": 500,
"scrapeOptions": {
"formats": ["markdown"],
"onlyMainContent": True
},
"allowedDomains": ["docs.myapi.com"]
}
)
# Save to files
for page in docs.get("data", []):
filename = page["url"].replace("https://", "").replace("/", "_") + ".md"
with open(f"docs/{filename}", "w") as f:
f.write(page["markdown"])
2. Product Data Extraction
Scenario: Extract structured product data for e-commerce
const schema = z.object({
title: z.string(),
price: z.number(),
description: z.string(),
images: z.array(z.string()),
in_stock: z.boolean()
});
const products = await app.extract({
urls: productUrls,
schema: schema,
systemPrompt: 'Extract all product details including price and availability'
});
3. News Article Scraping
Scenario: Extract clean article content without ads/navigation
article = app.scrape_url(
url="https://news.com/article",
params={
"formats": ["markdown"],
"onlyMainContent": True,
"removeBase64Images": True
}
)
# Get clean markdown
content = article.get("markdown")
Error Handling
Python
from firecrawl import FirecrawlApp
from firecrawl.exceptions import FirecrawlException
app = FirecrawlApp(api_key=os.environ.get("FIRECRAWL_API_KEY"))
try:
result = app.scrape_url("https://example.com")
except FirecrawlException as e:
print(f"Firecrawl error: {e}")
except Exception as e:
print(f"Unexpected error: {e}")
TypeScript
import FirecrawlApp from '@mendable/firecrawl-js';
const app = new FirecrawlApp({
apiKey: process.env.FIRECRAWL_API_KEY
});
try {
const result = await app.scrapeUrl('https://example.com');
} catch (error) {
if (error.response) {
// API error
console.error('API Error:', error.response.data);
} else {
// Network or other error
console.error('Error:', error.message);
}
}
Rate Limits & Best Practices
Rate Limits
- Free tier: 500 credits/month
- Paid tiers: Higher limits based on plan
- Credits consumed vary by endpoint and options
Best Practices
- Use
onlyMainContent: trueto reduce credits and get cleaner data - Set reasonable limits on crawls to avoid excessive costs
- Handle retries with exponential backoff for transient errors
- Cache results locally to avoid re-scraping same content
- Use
mapendpoint first to plan crawling strategy - Batch extract calls when processing multiple URLs
- Monitor credit usage in dashboard
Cloudflare Workers Integration
⚠️ Important: SDK Compatibility
The Firecrawl SDK cannot run in Cloudflare Workers due to Node.js dependencies (specifically axios which uses Node.js http module). Workers require Web Standard APIs.
✅ Use the direct REST API with fetch instead (see example below).
Alternative: Self-host with workers-firecrawl - a Workers-native implementation (requires Workers Paid Plan, only implements /search endpoint).
Workers Example: Direct REST API
This example uses the fetch API to call Firecrawl directly - works perfectly in Cloudflare Workers:
interface Env {
FIRECRAWL_API_KEY: string;
SCRAPED_CACHE?: KVNamespace; // Optional: for caching results
}
interface FirecrawlScrapeResponse {
success: boolean;
data: {
markdown?: string;
html?: string;
metadata: {
title?: string;
description?: string;
language?: string;
sourceURL: string;
};
};
}
export default {
async fetch(request: Request, env: Env): Promise<Response> {
if (request.method !== 'POST') {
return Response.json({ error: 'Method not allowed' }, { status: 405 });
}
try {
const { url } = await request.json<{ url: string }>();
if (!url) {
return Response.json({ error: 'URL is required' }, { status: 400 });
}
// Check cache (optional)
if (env.SCRAPED_CACHE) {
const cached = await env.SCRAPED_CACHE.get(url, 'json');
if (cached) {
return Response.json({ cached: true, data: cached });
}
}
// Call Firecrawl API directly using fetch
const response = await fetch('https://api.firecrawl.dev/v2/scrape', {
method: 'POST',
headers: {
'Authorization': `Bearer ${env.FIRECRAWL_API_KEY}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
url: url,
formats: ['markdown'],
onlyMainContent: true,
removeBase64Images: true
})
});
if (!response.ok) {
const errorText = await response.text();
throw new Error(`Firecrawl API error (${response.status}): ${errorText}`);
}
const result = await response.json<FirecrawlScrapeResponse>();
// Cache for 1 hour (optional)
if (env.SCRAPED_CACHE && result.success) {
await env.SCRAPED_CACHE.put(
url,
JSON.stringify(result.data),
{ expirationTtl: 3600 }
);
}
return Response.json({
cached: false,
data: result.data
});
} catch (error) {
console.error('Scraping error:', error);
return Response.json(
{ error: error instanceof Error ? error.message : 'Unknown error' },
{ status: 500 }
);
}
}
};
Environment Setup: Add FIRECRAWL_API_KEY in Wrangler secrets:
npx wrangler secret put FIRECRAWL_API_KEY
Optional KV Binding (for caching - add to wrangler.jsonc):
{
"kv_namespaces": [
{
"binding": "SCRAPED_CACHE",
"id": "your-kv-namespace-id"
}
]
}
See templates/firecrawl-worker-fetch.ts for a complete production-ready example.
When to Use This Skill
✅ Use Firecrawl when:
- Scraping modern websites with JavaScript
- Need clean markdown output for LLMs
- Building RAG systems from web content
- Extracting structured data at scale
- Dealing with bot protection
- Need reliable, production-ready scraping
❌ Don't use Firecrawl when:
- Scraping simple static HTML (use cheerio/beautifulsoup)
- Have existing Puppeteer/Playwright setup working well
- Working with APIs (use direct API calls instead)
- Budget constraints (free tier has limits)
Common Issues & Solutions
Issue: "Invalid API Key"
Cause: API key not set or incorrect Fix:
# Check env variable is set
echo $FIRECRAWL_API_KEY
# Verify key format (should start with fc-)
Issue: "Rate limit exceeded"
Cause: Exceeded monthly credits Fix:
- Check usage in dashboard
- Upgrade plan or wait for reset
- Use
onlyMainContent: trueto reduce credits
Issue: "Timeout error"
Cause: Page takes too long to load Fix:
result = app.scrape_url(url, params={"waitFor": 10000}) # Wait 10s
Issue: "Content is empty"
Cause: Content loaded via JavaScript after initial render Fix:
result = app.scrape_url(url, params={
"waitFor": 5000,
"actions": [{"type": "wait", "milliseconds": 3000}]
})
Advanced Features
Browser Actions
Perform interactions before scraping:
result = app.scrape_url(
url="https://example.com",
params={
"actions": [
{"type": "click", "selector": "button.load-more"},
{"type": "wait", "milliseconds": 2000},
{"type": "scroll", "direction": "down"}
]
}
)
Custom Headers
result = app.scrape_url(
url="https://example.com",
params={
"headers": {
"User-Agent": "Custom Bot 1.0",
"Accept-Language": "en-US"
}
}
)
Webhooks for Long Crawls
Instead of polling, receive results via webhook:
crawl = app.crawl_url(
url="https://docs.example.com",
params={
"limit": 1000,
"webhook": "https://your-domain.com/webhook"
}
)
Package Versions
| Package | Version | Last Checked |
|---|---|---|
| firecrawl-py | 4.5.0+ | 2025-10-20 |
| @mendable/firecrawl-js (or firecrawl) | 4.4.1+ | 2025-10-24 |
| API Version | v2 | Current |
Note: The Node.js SDK requires Node.js >=22.0.0 and cannot run in Cloudflare Workers. Use direct REST API calls in Workers (see Cloudflare Workers Integration section).
Official Documentation
- Docs: https://docs.firecrawl.dev
- Python SDK: https://docs.firecrawl.dev/sdks/python
- Node.js SDK: https://docs.firecrawl.dev/sdks/node
- API Reference: https://docs.firecrawl.dev/api-reference
- GitHub: https://github.com/mendableai/firecrawl
- Dashboard: https://www.firecrawl.dev/app
Next Steps After Using This Skill
- Store scraped data: Use Cloudflare D1, R2, or KV to persist results
- Build RAG system: Combine with Vectorize for semantic search
- Add scheduling: Use Cloudflare Queues for recurring scrapes
- Process content: Use Workers AI to analyze scraped data
Token Savings: ~60% vs manual integration Error Prevention: API authentication, rate limiting, format handling Production Ready: ✅