/agent by Firecrawl
While building mendable - we found that feeding LLMs well-structured markdown improved accuracy. We also found it surprisingly hard. We found some great tools online, but none reliably handled the entire process. We wanted an API that took a URL, crawled the pages in the URL, and gave us an easy-to-use, up-to-date markdown we could feed into our index. So, we released an open-source repo and an API that crawls and turns entire websites into a markdown with just a few lines of code The API handles: - Crawling without consistent sitemaps - Infra to handle running many crawling jobs - Proxying,…
/agent by Firecrawl launched on December 23, 2025 with 569 votes, #12 of 11,628 launches that month and more than 99% of that year's launches.
In plain words
Firecrawl /agent is an API that extracts structured data from websites by searching, navigating, and gathering information automatically. Users describe what data they need, and the tool retrieves it from complex or difficult-to-access web pages, returning either individual data points or large datasets. It's designed for developers who need to collect web data programmatically.
written from the facts on this page · September 2026
From the sources
Firecrawl /agent is a magic API that searches, navigates, and gathers data from even the most complex websites. Describe what data you want and agent handles the rest. Find information in hard-to-reach places, return single datapoints or entire datasets at scale.
Describe what data you want to extract and /agent handles the rest. Read the docs → from firecrawl import FirecrawlApp from pydantic import BaseModel from typing import List , Optional app = FirecrawlApp ( api_key =" fc-YOUR-API-KEY ") class Company ( BaseModel ): name: str founders: List [str] funding: Optional [str] = None website: str class ExtractSchema ( BaseModel ): companies: List [ Company ] result = app. agent ( prompt =" Get all YC W24 companies ", schema = ExtractSchema ) import { Firecrawl } from ' firecrawl '; import { z } from ' zod '; const firecrawl = new Firecrawl ({ apiKey : ' fc-YOUR-API-KEY ' }); const schema = z .object({ companies : z .array( z .object({ name : z…from firecrawl.dev
In the maker’s words, at launch
While building mendable - we found that feeding LLMs well-structured markdown improved accuracy. We also found it surprisingly hard. We found some great tools online, but none reliably handled the entire process. We wanted an API that took a URL, crawled the pages in the URL, and gave us an easy-to-use, up-to-date…
Does a similar job
all alternatives →
The new Firecrawl /searchJul 2026 · docs.firecrawl.dev · ▲257Our most accurate Search API for AI agents.


Firecrawl CLIMar 2026 · docs.firecrawl.dev · ▲249Firecrawl skills are an easy way for AI agents such as Codex, Claude Code, Cursor, and OpenCode to use Firecrawl through the CLI.
Firecrawl Research IndexJun 2026 · docs.firecrawl.dev · ▲221An index for agents pushing the frontier of AI/ML research
Web Search Agents by NimbleAug 2026 · nimbleway.com · ▲371Self-learning agents automate web research + retrieval
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