セットアップ
npm install @mendable/firecrawl-js openai zod
.env ファイルを作成：
FIRECRAWL_API_KEY=your_firecrawl_key
OPENAI_API_KEY=your_openai_key
注: Node < 20 を使用している場合は、dotenvをインストールし、コードにimport 'dotenv/config'を追加してください。
スクレイピング＋要約
import FirecrawlApp from '@mendable/firecrawl-js';
import OpenAI from 'openai';
const firecrawl = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY });
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
// ウェブサイトのコンテンツをスクレイピング
const scrapeResult = await firecrawl.scrape('https://firecrawl.dev', {
formats: ['markdown']
});
console.log('Scraped content length:', scrapeResult.markdown?.length);
// OpenAIモデルで要約
const completion = await openai.chat.completions.create({
model: 'gpt-5-nano',
messages: [
{ role: 'user', content: `Summarize: ${scrapeResult.markdown}` }
]
});
console.log('Summary:', completion.choices[0]?.message.content);
関数呼び出し
import FirecrawlApp from '@mendable/firecrawl-js';
import OpenAI from 'openai';
import { z } from 'zod';
const firecrawl = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY });
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const ScrapeArgsSchema = z.object({
url: z.string().describe('The URL of the website to scrape')
});
const tools = [{
type: 'function' as const,
function: {
name: 'scrape_website',
description: 'Scrape content from any website URL',
parameters: z.toJSONSchema(ScrapeArgsSchema)
}
}];
const response = await openai.chat.completions.create({
model: 'gpt-5-nano',
messages: [{
role: 'user',
content: 'What is Firecrawl? Visit firecrawl.dev and tell me about it.'
}],
tools
});
const message = response.choices[0]?.message;
if (message?.tool_calls && message.tool_calls.length > 0) {
for (const toolCall of message.tool_calls) {
if (toolCall.type === 'function') {
console.log('Tool called:', toolCall.function.name);
const args = ScrapeArgsSchema.parse(JSON.parse(toolCall.function.arguments));
const result = await firecrawl.scrape(args.url, {
formats: ['markdown'] // その他のフォーマット: html, links など
});
console.log('Scraped content:', result.markdown?.substring(0, 200) + '...');
// Send the scraped content back to the model for final response
const finalResponse = await openai.chat.completions.create({
model: 'gpt-5-nano',
messages: [
{
role: 'user',
content: 'What is Firecrawl? Visit firecrawl.dev and tell me about it.'
},
message,
{
role: 'tool',
tool_call_id: toolCall.id,
content: result.markdown || 'No content scraped'
}
],
tools
});
console.log('Final response:', finalResponse.choices[0]?.message?.content);
}
}
} else {
console.log('Direct response:', message?.content);
}
構造化データ抽出
import FirecrawlApp from '@mendable/firecrawl-js';
import OpenAI from 'openai';
import { z } from 'zod';
const firecrawl = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY });
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const scrapeResult = await firecrawl.scrape('https://stripe.com', {
formats: ['markdown']
});
console.log('Scraped content length:', scrapeResult.markdown?.length);
const CompanyInfoSchema = z.object({
name: z.string(),
industry: z.string(),
description: z.string(),
products: z.array(z.string())
});
const response = await openai.chat.completions.create({
model: 'gpt-5-nano',
messages: [
{
role: 'system',
content: 'Extract company information from website content.'
},
{
role: 'user',
content: `Extract data: ${scrapeResult.markdown}`
}
],
response_format: {
type: 'json_schema',
json_schema: {
name: 'company_info',
schema: z.toJSONSchema(CompanyInfoSchema),
strict: true
}
}
});
const content = response.choices[0]?.message?.content;
const companyInfo = content ? CompanyInfoSchema.parse(JSON.parse(content)) : null;
console.log('Validated company info:', companyInfo);
検索 + 分析
import FirecrawlApp from '@mendable/firecrawl-js';
import OpenAI from 'openai';
const firecrawl = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY });
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
// 関連情報を検索
const searchResult = await firecrawl.search('Next.js 16 new features', {
limit: 3,
sources: [{ type: 'web' }], // その他のソース: { type: 'news' }, { type: 'images' }
scrapeOptions: { formats: ['markdown'] }
});
console.log('Search results:', searchResult.web?.length, 'pages found');
// 主要機能を分析・要約
const analysis = await openai.chat.completions.create({
model: 'gpt-5-nano',
messages: [{
role: 'user',
content: `Summarize the key features: ${JSON.stringify(searchResult)}`
}]
});
console.log('Analysis:', analysis.choices[0]?.message?.content);
MCP を利用した Responses API
import OpenAI from 'openai';
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const response = await openai.responses.create({
model: 'gpt-5-nano',
tools: [
{
type: 'mcp',
server_label: 'firecrawl',
server_description: 'A web search and scraping MCP server to scrape and extract content from websites.',
server_url: `https://mcp.firecrawl.dev/${process.env.FIRECRAWL_API_KEY}/v2/mcp`,
require_approval: 'never'
}
],
input: 'Find out what the top stories on Hacker News are and the latest blog post on OpenAI and summarize them in a bullet point format'
});
console.log('Response:', JSON.stringify(response.output, null, 2));