- Specialization
- Data Engineering
- Business
Data Provisionand 1 more business valuesLess
- Agent Tooling
- Market
- Software Development
- Ecosystem
- Not classified
- Customers
Developersand 1 more customers valuesLess
- Enterprises
More details
- Organization type
- Commercial Company
- Ecosystem
- Not classified
- Business
- Data Provision, Agent Tooling
- Specialization
- Data Engineering
- Market
- Software Development
- Customers
- Developers, Enterprises
- Delivery models
- API
- Revenue models
- Usage Based
- Listing status
- Not classified
- Latest equity round
- Series A
- Reported funding amount
- $10M-$50M
About
Firecrawl builds an API that searches, scrapes, parses, and interacts with the live web, converting websites into clean, LLM-ready data. It sells primarily to AI companies, developers, and teams building agents, RAG pipelines, research tools, and other AI-native applications; its differentiation is scalable, real-time web context delivered through a single API.
Market
Firecrawl competes in web-data infrastructure and API services for AI agents and LLM applications, converting live, human-oriented websites into clean, structured context. Its positioning combines search, scraping, crawling, and browser interaction in one open-source and hosted API, with JavaScript-page support, proxy/orchestration handling, and LLM-ready Markdown or JSON output. Compared with search-first providers such as Exa and Tavily or marketplace-oriented Apify, Firecrawl differentiates through direct endpoints, broad extraction coverage, and an end-to-end workflow that can interact with pages before extracting data.
Primary customers are AI companies and developer or engineering teams building deep-research agents, RAG pipelines, AI assistants, lead-enrichment systems, competitive-intelligence tools, content-generation workflows, and price-monitoring applications. Firecrawl also targets enterprise and large-scale projects that need batch scraping, crawling, scheduled synchronization, and extraction across millions of pages.
At a Glance
Problem
AI applications need fresh, reliable web context, but the web is designed for human browsing rather than machine consumption. Websites are messy, dynamic, inconsistent, and often require navigation or interaction, forcing AI teams to build and maintain costly scraping, parsing, browser-automation, and data-refresh infrastructure. The central economic pain is engineering complexity and unreliable data: poor web context directly limits the quality of AI outputs.
The killer use case is enabling deep-research agents and other applications that need live information at scale. Firecrawl is aimed at teams building RAG pipelines, competitive-intelligence systems, lead-enrichment tools, price monitors, and content-generation products—anywhere an application must continuously find and understand current web information.
Product / Service
Firecrawl provides a context API and infrastructure layer for the live web. Its three core capabilities are Search, which finds relevant information; Scrape, which converts pages into clean, structured, LLM-ready data; and Interact, which lets systems click, navigate, and operate websites when simple extraction is insufficient. These capabilities can be used through APIs and are also exposed through an official MCP server, CLI, and agent-oriented integrations.
The service is delivered as a scalable, credit-based cloud product rather than software teams having to operate their own browser and scraping stack. Scrape, Crawl, Map, and Monitor consume credits per page, Search is priced per set of results, and Interact is priced by browser minute, with custom plans offering higher limits, support, security, and data-retention options. The benefit is a managed path from arbitrary web pages to usable AI context, with the ability to scale from individual experiments to production workloads.
Market
Firecrawl competes in the market for web data infrastructure, AI-native search, web scraping and crawling APIs, and browser interaction tools for AI agents. Its positioning is broader than a conventional scraper: it combines discovery, extraction, and web operation for systems that need to find, read, and act on live information. The company identifies Exa and Tavily as comparable AI-native search providers, while the wider competitive set includes traditional scraping, crawling, browser-automation, and data-access platforms.
Firecrawl has meaningful reported adoption rather than appearing pre-revenue in the available evidence: its site says more than 1.25 million developers and 150,000-plus companies use the product, and reports more than 400,000 MCP-server installations. It is also backed by Y Combinator and offers a free tier alongside paid Hobby, Standard, Growth, and custom plans. The available research does not disclose revenue or profitability, so those financial metrics cannot be assessed from the evidence.
Founders & Leadership
Funding History
Y Combinator
Nexus Venture Partners
Recent News
Firecrawl introduced Fireround, a company-funding data provider built by the company. It lets users follow funding rounds and research investors through Alexandria, with hourly updates and links to sources for each round.
Firecrawl introduced Universal Scrape, giving agents context from the web, files, and Alexandria providers through one Firecrawl API. The feature was described as a way to provide agents with a broader set of information sources through the scrape endpoint.
Firecrawl announced that Alexandria is available inside the ChatGPT plugin and that ChatGPT and Codex can reach more than 100 data providers and Firecrawl indexes alongside the live web. The same announcement also describes the Developer Index’s availability in Codex.
Firecrawl announced a $75 million Series B led by Smash Capital, with participation from Altos Ventures, Nexus Venture Partners, Y Combinator, Freestyle, and Offline Ventures. The company said the funding would support the expansion of Alexandria and its knowledge sources.
Firecrawl launched Alexandria, which brings official data providers, custom connectors, Firecrawl’s indexes, and the live web together for AI agents to discover sources and retrieve information. The product was announced alongside the company’s Series B.
Firecrawl was publicly reported as open-sourcing an AI adaptability testing tool with 12 website diagnostic metrics. The tool is intended to help evaluate how websites perform for AI agents and identify site-level issues affecting agent access and use.
Firecrawl announced that its web search capability was available through OpenRouter. The integration allows users to use Firecrawl as a web-search engine through OpenRouter's platform and grounds models with live, full-page, markdown-ready web content.
Firecrawl announced that it was live on the Vercel Marketplace as a native integration. The integration supports one-click installation, automatic API-key injection into the project environment, and billing through Vercel.
Firecrawl announced the Developer Index, a specialized index for coding agents. It contains more than 70 million artifacts—including READMEs, documentation, issues, pull requests, OpenAPI specifications and skills—with most sources refreshed daily, and is available through Firecrawl’s API, CLI, MCP and SDKs.
Firecrawl launched the Life Sciences category in its Research Index on August 13, 2026. The category covers more than 41 million papers across drug discovery, clinical trials, and biology, and is available through Firecrawl’s API, CLI, MCP, and SDKs.
Firecrawl launched an open-source agent stack for web research and extraction, allowing developers to scaffold, customize, and deploy their own web research agents.
Firecrawl announced a native integration with n8n Cloud, enabling users to bring real-time web data into AI workflows in a single step without API keys.
Firecrawl introduced Open Researcher, an AI research agent built with Anthropic’s interleaved thinking and Firecrawl tools, with no separate orchestration required.
Firecrawl announced that it had raised a $14.5 million Series A led by Nexus Venture Partners, citing a developer community of more than 350,000 people.
Active Roles
33Business Model
Firecrawl uses flexible, usage-based pricing: customers start with a free monthly allocation of credits and pay or scale through higher-volume plans as usage grows. API operations consume credits, with pricing varying by the volume and complexity of web searches, scrapes, and agent actions.
Products
Customers
Tech Stack
Similar Companies
Competitors
Key Investors
Nexus Venture Partners, Y Combinator, Shopify (Tobias Lutke)