Skip to content
Firecrawl MCP logo

Turn websites into LLM-ready data for AI applications with clean web scraping and crawling.

Visit Website
Tracked since2026
0 reviews tracked

The Bottom Line

Entry price

Free plan available, paid tiers above

Biggest pro

Provides clean, LLM-ready data for AI applications

Biggest con

Credits do not roll over to the next month on most plans

TL;DR - Firecrawl MCP

  • Scrapes and transforms web content into LLM-ready data for AI applications.
  • Offers comprehensive web scraping, searching, and browsing capabilities with high reliability and speed.
  • Open-source and easily integrates with AI agents and MCP clients.
Pricing: Free plan available
Best for: Growing teams

What is Firecrawl MCP?

Editorial review
Firecrawl is an open-source web data API designed to provide AI applications with clean, structured data from any website. It offers comprehensive web scraping and crawling capabilities, allowing users to extract content in various formats like Markdown, JSON, and screenshots. The platform is built for performance, offering high reliability and speed, covering a vast percentage of the web, including JavaScript-heavy pages, without requiring proxy management. Firecrawl is particularly suited for developers and AI agents who need real-time web data. It integrates seamlessly with AI agents and MCP clients, providing tools for scraping, searching, browsing, and mapping website URLs. The platform handles complex scraping challenges such as rotating proxies, orchestration, rate limits, and JavaScript-blocked content, allowing users to focus on leveraging the extracted data for their AI models and applications.

Available on: Web

Pros & Cons

Pros

  • Provides clean, LLM-ready data for AI applications
  • Open-source with a strong community and transparent development
  • High reliability covering 96% of the web, including JS-heavy pages
  • Blazingly fast with P95 latency of 3.4s
  • Handles complex scraping challenges like proxies and rate limits automatically

Cons

  • Credits do not roll over to the next month on most plans
  • Pay-per-use plan is not offered, only monthly subscriptions

Preview

Key Features

Scrape web pages into Markdown, JSON, or screenshotsSearch the web and retrieve full content from resultsBrowser sandboxes for AI agents to interact with the webMap all URLs of a websiteExtract data using AI promptsParse content from web-hosted PDFs and DOCX filesIntelligent waiting for content to load (Smart Wait)Interactive scraping actions (click, scroll, type, wait, press)

Pricing Plans

Pricing checked Jun 27, 2026

Free Plan

$0 one-time

  • 500 credits (one-time)
  • Scrape 500 pages
  • 2 concurrent requests
  • Low rate limits

Hobby

$16 / monthly

  • 3,000 credits / month
  • Scrape 3,000 pages
  • 5 concurrent requests
  • Basic support
  • $9 per extra 1k credits

Standard

$83 / monthly

  • 100,000 credits / month
  • Scrape 100,000 pages
  • 50 concurrent requests
  • Standard support
  • $47 per extra 35k credits

Growth

$333 / monthly

  • 500,000 credits / month
  • Scrape 500,000 pages
  • 100 concurrent requests
  • Priority support
  • $177 per extra 175k credits

Scale

$599 / month

  • 1,000,000 credits
  • Scrape 1,000,000 pages
  • 150 concurrent requests
  • Priority support

Enterprise

Contact sales

  • Custom credits
  • Scrape unlimited pages
  • Custom concurrent requests
  • Dedicated support & SLA
  • Bulk discounts
  • Zero-data retention
  • SSO & advanced security

Reviews

Improve Your Thinking Patterns Using ChatGPT cover
$99Free with your review

Review Firecrawl MCP, get a free AI guide

Share your experience and we will send you Improve Your Thinking Patterns Using ChatGPT, free.

Write a review

Best Firecrawl MCP Alternatives

Top alternatives based on features, pricing, and user needs.

Most buyers shortlist 2 or 3 tools before committing. Pull a side-by-side comparison or browse the full alternatives shortlist below.

Explore More

Firecrawl MCP FAQ

How does Firecrawl MCP assist AI applications with web data?

Firecrawl MCP is designed to turn websites into LLM-ready data, providing AI applications with clean, structured information. It offers comprehensive web scraping and crawling capabilities to extract content in formats like Markdown and JSON, which are suitable for AI models.

Which teams benefit most from using Firecrawl MCP?

Firecrawl MCP is particularly suited for developers and AI agents who require real-time web data for their applications. It helps these teams by handling complex scraping challenges, allowing them to focus on leveraging the extracted data for their AI models.

How does Firecrawl MCP compare to Apify for web scraping?

Firecrawl MCP provides clean, LLM-ready data specifically for AI applications, and is open-source with a strong community. It also boasts high reliability, covering 96% of the web including JavaScript-heavy pages, and handles complex scraping challenges automatically.

What kind of web content can Firecrawl MCP reliably process?

Firecrawl MCP offers high reliability, covering a vast percentage of the web, including JavaScript-heavy pages. It is built to handle complex scraping challenges such as rotating proxies, orchestration, and rate limits without requiring manual management.

Does Firecrawl MCP include a free tier?

Yes, Firecrawl MCP is available on a free tier, with paid plans offered for users who require more usage and additional features. It operates on a monthly subscription model rather than a pay-per-use plan.

What are the primary limitations of Firecrawl MCP's pricing structure?

A primary limitation of Firecrawl MCP's pricing structure is that credits do not roll over to the next month on most plans. Additionally, the platform does not offer a pay-per-use plan, only monthly subscriptions.

Can Firecrawl MCP integrate with existing AI agents?

Yes, Firecrawl MCP integrates seamlessly with AI agents and MCP clients. It provides tools for scraping, searching, browsing, and mapping website URLs, making it easy to incorporate web data into AI workflows.

Guides & Articles