← 返回
未分类 Key 中文

Firecrawl

AI-native web scraping, crawling, domain mapping, and structured extraction. Use for converting websites into LLM-ready Markdown, scraping pages with dynamic...
AI 原生网页抓取、爬取、域名映射和结构化提取。用于将网站转换为 LLM 可直接使用的 Markdown,爬取含动态内容的页面...
simonpierreboucher02 simonpierreboucher02 来源
未分类 clawhub v1.0.0 1 版本 100000 Key: 需要
★ 0
Stars
📥 165
下载
💾 0
安装
1
版本
#latest

概述

Firecrawl Skill

This skill extends Manus with the capability to search, scrape, crawl, and extract structured data from any website using Firecrawl [1] [2].

  • Author: Simon-Pierre Boucher
  • Target Audience: AI Engineers, Agent Developers, Data Engineers, Web Scraping Engineers

1. Core Workflows

1.1 Scraping a Single URL (/scrape)

Use when you need the text content, Markdown, HTML, or screenshots of a specific webpage [2].

  1. Initialize the Firecrawl client with your API key [1].
  2. Specify output formats (e.g., ["markdown"] or ["markdown", "screenshot"]) [2].
  3. Apply custom browser actions (e.g., click, wait, write) if the page has dynamic content or requires interaction [2].
  4. Optionally filter the DOM using includeTags or excludeTags [2].

1.2 Crawling a Domain (/crawl)

Use when you need to discover and scrape all pages under a specific domain or path recursively [1] [2].

  1. Start an asynchronous crawl job by specifying the starting url [2].
  2. Set depth limits (maxDepth) and page limits (limit) to control token and credit usage [2].
  3. Configure scrapeOptions to ensure each crawled page is parsed with the correct format (e.g., Markdown only) [2].
  4. Poll the crawl status using the jobId until completed [2].

1.3 Mapping a Domain (/map)

Use when you need to quickly discover all URLs belonging to a domain without scraping page content [1] [2].

  1. Provide the base url [2].
  2. Optionally provide a search filter to only return URLs matching a specific keyword or path [2].
  3. Set includeSubdomains to true if you need sub-domain discovery [2].

1.4 Structured Extraction (/extract)

Use when you need to parse raw web pages and extract structured JSON data conforming to a specific schema [3].

  1. Provide an array of urls and a natural language extraction prompt [3].
  2. Define the target schema using a JSON Schema, Pydantic model (Python), or Zod schema (TypeScript) [3].
  3. Run the extraction to retrieve guaranteed, type-safe JSON [3].

2. Resource Guides

For comprehensive API parameters, SDK code templates, and configuration options, read the following reference files:

  • API Reference & SDK Snippets: Read references/api_reference.md for complete endpoint request/response schemas, Python SDK templates, and TypeScript/Zod snippets.
  • Self-Hosting & Docker: Read references/self_hosting.md for production-ready Docker Compose configurations, environment variables, and scaling guidelines.

3. Best Practices & Anti-Patterns

3.1 Best Practices

  • Always use onlyMainContent: true to strip out navigation bars, headers, and footers. This dramatically reduces downstream LLM token costs and keeps context windows clean [2].
  • Leverage /map before /crawl if you only need to discover pages or filter specific URLs to scrape. Mapping is significantly faster and cheaper than full crawls [1] [2].
  • Implement exponential backoff with jitter when handling rate limits (429) or transient server errors (5xx) to ensure scraping resiliency [4].
  • Set explicit CPU and RAM limits on your containers if self-hosting to prevent headless Chromium from consuming all host system resources [5].

3.2 Anti-Patterns

  • Do not use hard-coded waitFor delays when scraping dynamic content. Instead, use selector-based waits (e.g., {"type": "wait", "selector": "#loaded-element"}) to minimize request latency [2].
  • Do not run synchronous crawls. Crawling is an inherently long-running process; always use the asynchronous /crawl endpoint and poll for results or use webhooks [2].
  • Do not reuse browser sessions across unrelated scraping tasks if security isolation is required. Firecrawl relies on ephemeral containers to prevent session contamination [5].

References

[1] Firecrawl Homepage, "The API to search, scrape, and interact with the web at scale." URL: https://github.com/firecrawl/firecrawl

[2] Firecrawl Documentation, "Advanced Scraping Guide." URL: https://docs.firecrawl.dev/advanced-scraping-guide

[3] Firecrawl Documentation, "Agent Endpoint." URL: https://docs.firecrawl.dev/features/agent

[4] Firecrawl Documentation, "Rate Limits." URL: https://docs.firecrawl.dev/rate-limits

[5] Firecrawl GitHub Repository, "Self-hosting Firecrawl Guide." URL: https://raw.githubusercontent.com/firecrawl/firecrawl/main/SELF_HOST.md

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-06-01 21:25

安全检测

腾讯云安全 (Keen)

队列中

腾讯云安全 (Sanbu)

队列中

🔗 相关推荐

data-analysis

Tavily 搜索

jacky1n7
通过 Tavily API 进行网页搜索(Brave 替代方案)。当用户要求搜索网页、查找来源或链接,且 Brave 网页搜索不可用时使用。
★ 275 📥 101,187
data-analysis

Data Analysis

ivangdavila
{"answer":"数据分析与可视化。查询数据库、生成报告、自动化电子表格,将原始数据转化为清晰可行的见解。适用于:(1) 您……"}
★ 212 📥 70,788
dev-programming

anthropic api

simonpierreboucher02
集成Anthropic Claude API,实现聊天、工具、视觉、文档分析与代码生成,兼顾成本控制和错误处理。
★ 0 📥 284