Firecrawl▌

--- # **🔥 Firecrawl** **Turn websites into LLM-ready data.** [**Firecrawl**](https://firecrawl.dev/?ref=github) 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](https://github.com/firecrawl/firecrawl-mcp-server). *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](https://www.firecrawl.dev/blog/the-worlds-best-web-data-api-v25), 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 Sign up at [firecrawl.dev](https://firecrawl.dev) to get your API key and start extracting data in seconds. Try the [playground](https://firecrawl.dev/playground) to test it out. ### Make Your First API Request ```bash 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: ```json { "success": true, "data": { "markdown": "# Example Domain This domain is for use in illustrative examples...", "metadata": { "title": "Example Domain", "sourceURL": "https://example.com" } } } ``` --- ## Feature Overview | Feature | Description | |---------|-------------| | [**Scrape**](#scraping) | Convert any URL to markdown, HTML, screenshots, or structured JSON | | [**Search**](#search) | Search the web and get full page content from results | | [**Map**](#map) | Discover all URLs on a website instantly | | [**Crawl**](#crawling) | Scrape all URLs of a website with a single request | | [**Agent**](#agent) | Automated data gathering, just describe what you need | --- ## Scrape Convert any URL to clean markdown, HTML, or structured data. ```bash 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: ```json { "success": true, "data": { "markdown": "# Firecrawl Docs Turn websites into LLM-ready data...", "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: ```python 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) ``` ```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): ```python 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** ```python doc = app.scrape("https://firecrawl.dev", formats=["screenshot"]) print(doc.screenshot) # Base64 encoded image ``` **Extract brand identity (colors, fonts, typography)** ```python 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: ```python doc = app.scrape( url="https://example.com/login", formats=["markdown"], actions=[ {"type": "write", "text": "user@example.com"}, {"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. ```bash 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: ```json { "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: ```python 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. ```bash 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: ```json { "success": true, "data": { "result": "Notion offers the following pricing plans: 1. Free - $0/month... 2. Plus - $10/seat/month... 3. Business - $18/seat/month...", "sources": ["https://www.notion.so/pricing"] } } ``` ### Agent with Structured Output Use a schema to get structured data: ```python 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) ``` ```json { "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: ```python 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 | ```python 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 [Agen ---