# Firecrawl: Web Scraping and Interaction API for AI Agents

This repository profile is provided by osrepos.com, an open source repository discovery platform.

Source: osrepos.com
Repository profile: https://osrepos.com/repo/mendableai-firecrawl
Generated for open source discovery and AI-assisted research.

Firecrawl is an open-source API designed to empower AI agents and applications with clean, structured web data. It provides robust capabilities for searching, scraping, and interacting with the web at scale, effectively transforming complex web content into LLM-ready formats. This tool handles the intricate challenges of web data extraction, allowing developers to focus on building intelligent applications.

GitHub: https://github.com/mendableai/firecrawl
OSRepos URL: https://osrepos.com/repo/mendableai-firecrawl

## Summary

Firecrawl is an open-source API designed to empower AI agents and applications with clean, structured web data. It provides robust capabilities for searching, scraping, and interacting with the web at scale, effectively transforming complex web content into LLM-ready formats. This tool handles the intricate challenges of web data extraction, allowing developers to focus on building intelligent applications.

## Topics

- AI
- Web Scraping
- Data Extraction
- LLM
- AI Agents
- Crawler
- TypeScript
- API

## Repository Information

Last analyzed by OSRepos: Wed May 13 2026 08:58:19 GMT+0100 (Western European Summer Time)
Detail views: 4
GitHub clicks: 18

## Safety Notice

OSRepos shares public repositories for knowledge and discovery only. Review source code, dependencies, licenses, and security implications before running or installing anything.

## Content

## Introduction

Firecrawl is an open-source API designed to empower AI agents and applications with clean, structured web data. It provides robust capabilities for searching, scraping, and interacting with the web at scale, effectively transforming complex web content into LLM-ready formats like Markdown or JSON. Firecrawl handles the intricate challenges of web data extraction, including JavaScript-heavy pages, rotating proxies, and rate limits, allowing developers to focus on building intelligent applications.

For more details, visit the official [GitHub repository](https://github.com/firecrawl/firecrawl){:target="_blank"} or the [Firecrawl website](https://firecrawl.dev){:target="_blank"}.

## Installation

Getting started with Firecrawl is straightforward, especially with its Python SDK. First, you'll need an API key from [firecrawl.dev](https://firecrawl.dev){:target="_blank"}. Then, install the Python SDK using pip:

bash
pip install firecrawl-py


## Examples

Here are some quick examples demonstrating Firecrawl's core functionalities using the Python SDK:

### Search

Search the web and retrieve full content from the results.

python
from firecrawl import Firecrawl

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

search_result = app.search("firecrawl", limit=5)
# Output will be a list of dictionaries with url, title, and markdown content


### Scrape

Convert any URL into LLM-ready data, such as Markdown, JSON, or screenshots.

python
from firecrawl import Firecrawl

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

result = app.scrape('firecrawl.dev')
# The result object contains the scraped content in markdown and other formats


### Agent

The Agent feature allows you to describe what data you need, and Firecrawl's AI agent will autonomously search, navigate, and retrieve it, without requiring specific URLs upfront.

python
from firecrawl import Firecrawl

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

result = app.agent(
    prompt="Find the pricing plans for Notion"
)
# result.data will contain the extracted pricing information


## Why Use Firecrawl?

Firecrawl stands out for several reasons, making it an excellent choice for AI-driven web data needs:

*   **Industry-leading reliability:** It covers 96% of the web, including challenging JavaScript-heavy pages, ensuring consistent data extraction without proxy management headaches.
*   **Blazingly fast:** With a P95 latency of 3.4s across millions of pages, it's optimized for real-time agents and dynamic applications.
*   **LLM-ready output:** Provides clean Markdown, structured JSON, and screenshots, reducing token usage and improving the quality of AI applications.
*   **Handles the hard stuff:** Automatically manages rotating proxies, orchestration, rate limits, and JS-blocked content, requiring zero configuration from the user.
*   **Agent ready:** Easily connects to any AI agent or MCP client with simple commands.
*   **Open source:** Developed transparently and collaboratively, fostering a strong community.

## Links

*   **GitHub Repository:** [firecrawl/firecrawl](https://github.com/firecrawl/firecrawl){:target="_blank"}
*   **Official Website:** [firecrawl.dev](https://firecrawl.dev){:target="_blank"}
*   **Documentation:** [Firecrawl Docs](https://docs.firecrawl.dev){:target="_blank"}
*   **API Reference:** [Firecrawl API Reference](https://docs.firecrawl.dev/api-reference/introduction){:target="_blank"}
*   **Playground:** [Firecrawl Playground](https://firecrawl.dev/playground){:target="_blank"}