FirecrawlScrape

The FirecrawlScrape tool extracts data from a single webpage and supports multiple output formats including markdown, HTML, JSON, screenshots, and AI-powered structured data extraction.

Overview

FirecrawlScrape is perfect for extracting content from individual web pages with precision and flexibility. Whether you need clean markdown content, structured data, or visual screenshots, this tool provides comprehensive extraction capabilities.

Input Parameters

Parameter	Type	Required	Default	Description
`url`	string	Yes	-	URL of the website to be scraped
`formats`	string[]	Yes	`["markdown", "html"]`	List of content formats to extract. Valid values: `"markdown"`, `"html"`, `"json"`, `"links"`, `"screenshot"`, `"screenshot@fullPage"`, `"rawHtml"`
`prompt`	string	No	-	A natural language instruction used for schema-less extraction. The LLM will interpret the prompt and return relevant structured data from the page
`schema`	object	No	-	A JSON schema that defines the structure and data types to extract from the webpage for precise, structured extraction

Available Formats

The formats parameter accepts the following values:

Content Formats

"markdown" - Clean markdown representation of the page content
"html" - Cleaned and formatted HTML content
"rawHtml" - Complete raw HTML source code
"json" - Structured JSON data (used with schemas or prompts)

Link and Media Formats

"links" - All links found on the page
"screenshot" - Screenshot of the visible page area
"screenshot@fullPage" - Full-page screenshot including content below the fold

Basic Usage

Simple Content Extraction

To extract basic content from a webpage:

Enter the URL: Input the target webpage URL in the URL field
Select Formats: Choose the desired output formats (markdown, HTML, etc.)
Run the Task: Execute the scraping operation

Example Configuration:

URL: https://example.com
Formats: ["markdown", "html", "links"]

Schema-Based Structured Extraction

Define a precise schema for structured data extraction to get specific information in a predictable format.

How to Configure Schema Extraction

Add JSON Format: Include "json" in your formats selection
Define Schema: Specify the data structure you want to extract
Set Data Types: Use appropriate types (string, number, boolean, array, object)

Example Schema for Company Information:

{
  "company_mission": "string",
  "supports_sso": "boolean",
  "is_open_source": "boolean",
  "is_in_yc": "boolean",
  "employee_count": "number",
  "funding_rounds": "array"
}

When using schema-based extraction, make sure to include "json" in the formats array. The schema defines the exact structure and data types you want to extract from the webpage.

Advanced Schema Examples

Product Information Extraction

{
  "product_name": "string",
  "price": "number",
  "currency": "string",
  "in_stock": "boolean",
  "features": "array",
  "rating": "number",
  "reviews_count": "number",
  "images": "array"
}

Company Information Extraction

{
  "company_name": "string",
  "industry": "string",
  "headquarters": "string",
  "founded_year": "number",
  "employee_count": "string",
  "revenue": "string",
  "key_executives": "array",
  "contact_info": "object"
}

Prompt-Based Extraction

For flexible data extraction without predefined schemas, use natural language prompts to describe what information you want to extract.

How to Configure Prompt Extraction

Add JSON Format: Include "json" in your formats selection
Write Clear Prompt: Describe what information you want to extract
Be Specific: The more specific your prompt, the better the results

Example Prompt:

"Extract the main article title, author, publication date, key points, and any mentioned statistics or data points from this webpage"

Effective Prompt Examples

Content Analysis

"Summarize the main topics discussed, identify key stakeholders mentioned, and extract any numerical data or statistics"

Contact Information

"Find all contact information including emails, phone numbers, addresses, and social media links"

Product Features

"List all product features, pricing information, and customer testimonials or reviews"

Response Format

The scraping tool returns structured data based on your configuration:

{
  "data": {
    "markdown": "# Page content in markdown format...",
    "html": "<div>Cleaned HTML content...</div>",
    "json": {
      "company_mission": "To revolutionize web scraping",
      "supports_sso": true,
      "is_open_source": false
    },
    "rawHtml": "<!DOCTYPE html><html>Complete raw HTML...</html>",
    "screenshot": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA...",
    "links": [
      "https://example.com/about",
      "https://example.com/contact",
      "https://example.com/pricing"
    ],
    "title": "Example Company - Homepage",
    "description": "Leading provider of web scraping solutions",
    "language": "en",
    "keywords": ["web scraping", "automation", "data extraction"]
  },
  "status": "success",
  "message": "Successfully scraped the website"
}

Use Cases

📊 Content Extraction

Extract blog posts, articles, and documentation:

URL: https://blog.example.com/latest-post
Formats: ["markdown", "json"]

Schema:

{
  "title": "string",
  "author": "string",
  "published_date": "string",
  "content": "string",
  "tags": "array"
}

🏢 Business Information

Extract company details and information:

URL: https://company.com/about
Formats: ["json"]
Prompt: "Extract company name, mission, team size, contact information, and key services offered"

🛍️ Product Analysis

Extract product information from e-commerce sites:

URL: https://store.com/product/123
Formats: ["json", "screenshot"]

Schema:

{
  "name": "string",
  "price": "number",
  "availability": "boolean",
  "features": "array",
  "rating": "number"
}

📸 Visual Documentation

Capture page screenshots and structure:

URL: https://example.com
Formats: ["screenshot@fullPage", "links", "markdown"]

Best Practices

⚡ Performance Tips

Choose Appropriate Formats
- Only request formats you actually need
- Use "screenshot" instead of "screenshot@fullPage" for large pages
Use Specific Schemas
- Define precise data structures for better accuracy
- Use appropriate data types (number, boolean, array)
Craft Clear Prompts
- Be specific about what information you want
- Avoid overly broad or vague instructions

🎯 Extraction Accuracy

URL Format
- ✅ Always include the protocol: https://example.com
- ❌ Avoid incomplete URLs: example.com
Schema Data Types
- ✅ Use "number" for numerical data
- ✅ Use "boolean" for true/false values
- ✅ Use "array" for lists
Format Selection
- ✅ Always specify required formats
- ❌ Don’t leave formats empty

Common Issues and Solutions

URL Format Errors

Problem: Missing protocol in URL
Solution: Always include https:// or http://

Missing Required Formats

Problem: No formats selected
Solution: Always specify at least one output format

Schema Type Mismatches

Problem: Using wrong data types in schema
Solution: Match data types to expected content (string, number, boolean, array)

Poor Extraction Results

Problem: Vague prompts or overly complex schemas
Solution: Be specific and clear in prompts, keep schemas focused

Next: Learn Crawling

Explore multi-page website crawling with FirecrawlCrawl

​FirecrawlScrape

​Overview

​Input Parameters

​Available Formats

​Content Formats

​Link and Media Formats

​Basic Usage

​Simple Content Extraction

​Schema-Based Structured Extraction

​How to Configure Schema Extraction

​Advanced Schema Examples

​Product Information Extraction

​Company Information Extraction

​Prompt-Based Extraction

​How to Configure Prompt Extraction

​Effective Prompt Examples

​Content Analysis

​Contact Information

​Product Features

​Response Format

​Use Cases

​📊 Content Extraction

​🏢 Business Information

​🛍️ Product Analysis

​📸 Visual Documentation

​Best Practices

​⚡ Performance Tips

​🎯 Extraction Accuracy

​Common Issues and Solutions

​URL Format Errors

​Missing Required Formats

​Schema Type Mismatches

​Poor Extraction Results

Next: Learn Crawling

FirecrawlScrape

Overview

Input Parameters

Available Formats

Content Formats

Link and Media Formats

Basic Usage

Simple Content Extraction

Schema-Based Structured Extraction

How to Configure Schema Extraction

Advanced Schema Examples

Product Information Extraction

Company Information Extraction

Prompt-Based Extraction

How to Configure Prompt Extraction

Effective Prompt Examples

Content Analysis

Contact Information

Product Features

Response Format

Use Cases

📊 Content Extraction

🏢 Business Information

🛍️ Product Analysis

📸 Visual Documentation

Best Practices

⚡ Performance Tips

🎯 Extraction Accuracy

Common Issues and Solutions

URL Format Errors

Missing Required Formats

Schema Type Mismatches

Poor Extraction Results