WEB SEARCH API
FOR AI BUILDERS

Register Prismfy as a MCP tool so Claude can browse the web during your coding sessions without leaving the terminal.

// .claude/settings.json
{
  "mcpServers": {
    "prismfy": {
      "command": "npx prismfy-mcp",
      "env": {
        "PRISMFY_API_KEY": "ss_live_..."
      }
    }
  }
}

Expose Prismfy as a tool to GPT-4o, Claude or Gemini. Your agent calls real-time web search only when it needs fresh data.

import { Prismfy } from '@prismfy/prismfy'

const client = new Prismfy({ apiKey: 'ss_live_...' })

// tool handler
async function web_search({ query }) {
  const result = await client.search(query)
  return result.results.map(r => ({
    title: r.title, url: r.url,
    snippet: r.content
  }))
}

Build scripts that automatically search, qualify and enrich company data — funding rounds, hiring signals, news — all in one pipeline.

from prismfy import Prismfy

client = Prismfy(api_key="ss_live_...")
companies = ["Stripe", "Linear", "Vercel"]

for name in companies:
    result = client.search(
        f"{name} funding CEO latest news",
        engines=["google", "hackernews", "reddit"]
    )
    sheet.append_row([name, result.results[0].url])

Fetch fresh web results before every LLM call. Keep your knowledge base current without manual updates or expensive re-indexing.

from prismfy import Prismfy

client = Prismfy()  # reads PRISMFY_API_KEY from env

def get_context(query: str) -> str:
    result = client.search(
        query,
        engines=["google", "arxiv"],
        time_range="week"
    )
    return "\n".join(
        f"{r.title}: {r.content[:300]}"
        for r in result.results
    )

Schedule keyword searches on a cron, pipe results into Slack, Discord or your AI pipeline. Never miss a competitor move or market signal.

from prismfy import Prismfy

client = Prismfy(api_key="ss_live_...")

# runs every 15 min via cron
result = client.search(
    "OpenAI GPT-5 release date",
    engines=["google", "hackernews", "reddit"],
    time_range="day"
)
if result.results:
    slack.post(result.results[0].title)

Combine Prismfy with any LLM to ship answer engines, research assistants, or chatbots with live web access in under a day.

import { Prismfy } from '@prismfy/prismfy'
import OpenAI from 'openai'

const search = new Prismfy({ apiKey: 'ss_live_...' })
const openai = new OpenAI()

const result = await search.search(userQuery)
const context = result.results
  .map(r => `${r.title}\n${r.content}`).join('\n\n')

const answer = await openai.chat.completions.create({
  model: 'gpt-4o',
  messages: [{ role: 'user',
    content: `${context}\n\nQ: ${userQuery}` }]
})