firecrawl

🔥 The Web Data API for AI - Turn entire websites into LLM-ready markdown or structured data

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Firecrawl is an API service that empowers AI applications with clean data from any website. It features advanced scraping, crawling, and data extraction capabilities. The repository is still in development, integrating custom modules into the mono repo. Users can run it locally but it's not fully ready for self-hosted deployment yet. Firecrawl offers powerful capabilities like scraping, crawling, mapping, searching, and extracting structured data from single pages, multiple pages, or entire websites with AI. It supports various formats, actions, and batch scraping. The tool is designed to handle proxies, anti-bot mechanisms, dynamic content, media parsing, change tracking, and more. Firecrawl is available as an open-source project under the AGPL-3.0 license, with additional features offered in the cloud version.

README:

🔥 Firecrawl

Turn websites into LLM-ready data.

Firecrawl is an API that scrapes, crawls, and extracts structured data from any website, powering AI agents and apps with real-time context from the web.

Looking for our MCP? Check out the repo here.

This repository is in development, and we're still integrating custom modules into the mono repo. It's not fully ready for self-hosted deployment yet, but you can run it locally.

Pst. Hey, you, join our stargazers :)

Why Firecrawl?

LLM-ready output: Clean markdown, structured JSON, screenshots, HTML, and more
Industry-leading reliability: >80% coverage on benchmark evaluations, outperforming every other provider tested
Handles the hard stuff: Proxies, JavaScript rendering, and dynamic content that breaks other scrapers
Customization: Exclude tags, crawl behind auth walls, max depth, and more
Media parsing: Automatic text extraction from PDFs, DOCX, and images
Actions: Click, scroll, input, wait, and more before extracting
Batch processing: Scrape thousands of URLs asynchronously
Change tracking: Monitor website content changes over time

Quick Start

Make Your First API Request

curl -X POST 'https://api.firecrawl.dev/v2/scrape' \
  -H 'Authorization: Bearer fc-YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{"url": "https://example.com"}'

Response:

{
  "success": true,
  "data": {
    "markdown": "# Example Domain\n\nThis domain is for use in illustrative examples...",
    "metadata": {
      "title": "Example Domain",
      "sourceURL": "https://example.com"
    }
  }
}

Feature Overview

Feature	Description
Scrape	Convert any URL to markdown, HTML, screenshots, or structured JSON
Search	Search the web and get full page content from results
Agent	Automated data gathering, just describe what you need
Crawl	Scrape all URLs of a website with a single request
Map	Discover all URLs on a website instantly

Scrape

Convert any URL to clean markdown, HTML, or structured data.

curl -X POST 'https://api.firecrawl.dev/v2/scrape' \
  -H 'Authorization: Bearer fc-YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "url": "https://docs.firecrawl.dev",
    "formats": ["markdown", "html"]
  }'

Response:

{
  "success": true,
  "data": {
    "markdown": "# Firecrawl Docs\n\nTurn websites into LLM-ready data...",
    "html": "<!DOCTYPE html><html>...",
    "metadata": {
      "title": "Quickstart | Firecrawl",
      "description": "Firecrawl allows you to turn entire websites into LLM-ready markdown",
      "sourceURL": "https://docs.firecrawl.dev",
      "statusCode": 200
    }
  }
}

Extract Structured Data (JSON Mode)

Extract structured data using a schema:

from firecrawl import Firecrawl
from pydantic import BaseModel

app = Firecrawl(api_key="fc-YOUR_API_KEY")

class CompanyInfo(BaseModel):
    company_mission: str
    is_open_source: bool
    is_in_yc: bool

result = app.scrape(
    'https://firecrawl.dev',
    formats=[{"type": "json", "schema": CompanyInfo.model_json_schema()}]
)

print(result.json)

{"company_mission": "Turn websites into LLM-ready data", "is_open_source": true, "is_in_yc": true}

Or extract with just a prompt (no schema):

result = app.scrape(
    'https://firecrawl.dev',
    formats=[{"type": "json", "prompt": "Extract the company mission"}]
)

Scrape Formats

Available formats: markdown, html, rawHtml, screenshot, links, json, branding

Get a screenshot

doc = app.scrape("https://firecrawl.dev", formats=["screenshot"])
print(doc.screenshot)  # Base64 encoded image

Extract brand identity (colors, fonts, typography)

doc = app.scrape("https://firecrawl.dev", formats=["branding"])
print(doc.branding)  # {"colors": {...}, "fonts": [...], "typography": {...}}

Actions (Interact Before Scraping)

Click, type, scroll, and more before extracting:

doc = app.scrape(
    url="https://example.com/login",
    formats=["markdown"],
    actions=[
        {"type": "write", "text": "[email protected]"},
        {"type": "press", "key": "Tab"},
        {"type": "write", "text": "password"},
        {"type": "click", "selector": 'button[type="submit"]'},
        {"type": "wait", "milliseconds": 2000},
        {"type": "screenshot"}
    ]
)

Search

Search the web and optionally scrape the results.

curl -X POST 'https://api.firecrawl.dev/v2/search' \
  -H 'Authorization: Bearer fc-YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "query": "firecrawl web scraping",
    "limit": 5
  }'

Response:

{
  "success": true,
  "data": {
    "web": [
      {
        "url": "https://www.firecrawl.dev/",
        "title": "Firecrawl - The Web Data API for AI",
        "description": "The web crawling, scraping, and search API for AI.",
        "position": 1
      }
    ],
    "images": [...],
    "news": [...]
  }
}

Search with Content Scraping

Get the full content of search results:

from firecrawl import Firecrawl

firecrawl = Firecrawl(api_key="fc-YOUR_API_KEY")

results = firecrawl.search(
    "firecrawl web scraping",
    limit=3,
    scrape_options={
        "formats": ["markdown", "links"]
    }
)

Agent

The easiest way to get data from the web. Describe what you need, and our AI agent searches, navigates, and extracts it. No URLs required.

Agent is the evolution of our /extract endpoint: faster, more reliable, and doesn't require you to know the URLs upfront.

curl -X POST 'https://api.firecrawl.dev/v2/agent' \
  -H 'Authorization: Bearer fc-YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "prompt": "Find the pricing plans for Notion"
  }'

Response:

{
  "success": true,
  "data": {
    "result": "Notion offers the following pricing plans:\n\n1. Free - $0/month...\n2. Plus - $10/seat/month...\n3. Business - $18/seat/month...",
    "sources": ["https://www.notion.so/pricing"]
  }
}

Agent with Structured Output

Use a schema to get structured data:

from firecrawl import Firecrawl
from pydantic import BaseModel, Field
from typing import List, Optional

app = Firecrawl(api_key="fc-YOUR_API_KEY")

class Founder(BaseModel):
    name: str = Field(description="Full name of the founder")
    role: Optional[str] = Field(None, description="Role or position")

class FoundersSchema(BaseModel):
    founders: List[Founder] = Field(description="List of founders")

result = app.agent(
    prompt="Find the founders of Firecrawl",
    schema=FoundersSchema
)

print(result.data)

{
  "founders": [
    {"name": "Eric Ciarla", "role": "Co-founder"},
    {"name": "Nicolas Camara", "role": "Co-founder"},
    {"name": "Caleb Peffer", "role": "Co-founder"}
  ]
}

Agent with URLs (Optional)

Focus the agent on specific pages:

result = app.agent(
    urls=["https://docs.firecrawl.dev", "https://firecrawl.dev/pricing"],
    prompt="Compare the features and pricing information"
)

Model Selection

Choose between two models based on your needs:

Model	Cost	Best For
`spark-1-mini` (default)	60% cheaper	Most tasks
`spark-1-pro`	Standard	Complex research, critical extraction

result = app.agent(
    prompt="Compare enterprise features across Firecrawl, Apify, and ScrapingBee",
    model="spark-1-pro"
)

When to use Pro:

Comparing data across multiple websites
Extracting from sites with complex navigation or auth
Research tasks where the agent needs to explore multiple paths
Critical data where accuracy is paramount

Learn more about Spark models in our Agent documentation.

Using Firecrawl with AI agents

Install the Firecrawl skill to let AI agents like Claude Code, Codex, and OpenCode use Firecrawl automatically:

npx skills add firecrawl/cli

Restart your agent after installing. See the Skill + CLI docs for full setup.

Crawling

Crawl an entire website and get content from all pages.

curl -X POST 'https://api.firecrawl.dev/v2/crawl' \
  -H 'Authorization: Bearer fc-YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "url": "https://docs.firecrawl.dev",
    "limit": 100,
    "scrapeOptions": {
      "formats": ["markdown"]
    }
  }'

Returns a job ID:

{
  "success": true,
  "id": "123-456-789",
  "url": "https://api.firecrawl.dev/v2/crawl/123-456-789"
}

Check Crawl Status

curl -X GET 'https://api.firecrawl.dev/v2/crawl/123-456-789' \
  -H 'Authorization: Bearer fc-YOUR_API_KEY'

{
  "status": "completed",
  "total": 50,
  "completed": 50,
  "creditsUsed": 50,
  "data": [
    {
      "markdown": "# Page Title\n\nContent...",
      "metadata": {"title": "Page Title", "sourceURL": "https://..."}
    }
  ]
}

Note: The SDKs handle polling automatically for a better developer experience.

Map

Discover all URLs on a website instantly.

curl -X POST 'https://api.firecrawl.dev/v2/map' \
  -H 'Authorization: Bearer fc-YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{"url": "https://firecrawl.dev"}'

Response:

{
  "success": true,
  "links": [
    {"url": "https://firecrawl.dev", "title": "Firecrawl", "description": "Turn websites into LLM-ready data"},
    {"url": "https://firecrawl.dev/pricing", "title": "Pricing", "description": "Firecrawl pricing plans"},
    {"url": "https://firecrawl.dev/blog", "title": "Blog", "description": "Firecrawl blog"}
  ]
}

Map with Search

Find specific URLs within a site:

from firecrawl import Firecrawl

app = Firecrawl(api_key="fc-YOUR_API_KEY")

result = app.map("https://firecrawl.dev", search="pricing")
# Returns URLs ordered by relevance to "pricing"

Batch Scraping

Scrape multiple URLs at once:

from firecrawl import Firecrawl

app = Firecrawl(api_key="fc-YOUR_API_KEY")

job = app.batch_scrape([
    "https://firecrawl.dev",
    "https://docs.firecrawl.dev",
    "https://firecrawl.dev/pricing"
], formats=["markdown"])

for doc in job.data:
    print(doc.metadata.source_url)

SDKs

Our SDKs provide a convenient way to interact with all Firecrawl features and automatically handle polling for async operations like crawling and batch scraping.

Python

Install the SDK:

pip install firecrawl-py

from firecrawl import Firecrawl

app = Firecrawl(api_key="fc-YOUR_API_KEY")

# Scrape a single URL
doc = app.scrape("https://firecrawl.dev", formats=["markdown"])
print(doc.markdown)

# Use the Agent for autonomous data gathering
result = app.agent(prompt="Find the founders of Stripe")
print(result.data)

# Crawl a website (automatically waits for completion)
docs = app.crawl("https://docs.firecrawl.dev", limit=50)
for doc in docs.data:
    print(doc.metadata.source_url, doc.markdown[:100])

# Search the web
results = app.search("best web scraping tools 2024", limit=10)
print(results)

Node.js

Install the SDK:

npm install @mendable/firecrawl-js

import Firecrawl from '@mendable/firecrawl-js';

const app = new Firecrawl({ apiKey: 'fc-YOUR_API_KEY' });

// Scrape a single URL
const doc = await app.scrape('https://firecrawl.dev', { formats: ['markdown'] });
console.log(doc.markdown);

// Use the Agent for autonomous data gathering
const result = await app.agent({ prompt: 'Find the founders of Stripe' });
console.log(result.data);

// Crawl a website (automatically waits for completion)
const docs = await app.crawl('https://docs.firecrawl.dev', { limit: 50 });
docs.data.forEach(doc => {
    console.log(doc.metadata.sourceURL, doc.markdown.substring(0, 100));
});

// Search the web
const results = await app.search('best web scraping tools 2024', { limit: 10 });
results.data.web.forEach(result => {
    console.log(`${result.title}: ${result.url}`);
});

Community SDKs

Integrations

Agents & AI Tools

Platforms

View all integrations →

Missing your favorite tool? Open an issue and let us know!

Resources

Open Source vs Cloud

Firecrawl is open source under the AGPL-3.0 license. The cloud version at firecrawl.dev includes additional features:

To run locally, see the Contributing Guide. To self-host, see Self-Hosting Guide.

Contributing

We love contributions! Please read our Contributing Guide before submitting a pull request.

Contributors

License

This project is primarily licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). The SDKs and some UI components are licensed under the MIT License. See the LICENSE files in specific directories for details.

It is the sole responsibility of end users to respect websites' policies when scraping. Users are advised to adhere to applicable privacy policies and terms of use. By default, Firecrawl respects robots.txt directives. By using Firecrawl, you agree to comply with these conditions.

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Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.

github

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