Agent Context Bridge Workflow

import requests
import json
from pathlib import Path
from datetime import datetime

API_KEY = "your_scavio_api_key"

# Queries that agents commonly use
AGENT_QUERIES = [
    "best search API for AI agents 2026",
    "web search API pricing comparison",
    "structured SERP data providers",
    "MCP search tool integration",
    "AI agent web grounding methods",
]

def fetch_and_compress(query: str) -> dict:
    res = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": API_KEY},
        json={"platform": "google", "query": query, "ai_overview": True},
        timeout=15,
    )
    res.raise_for_status()
    data = res.json()

    # Compress for agent consumption: only essential fields
    return {
        "q": query,
        "organic": [
            {"t": r.get("title", "")[:80], "s": r.get("snippet", "")[:150], "u": r.get("link", "")}
            for r in data.get("organic", [])[:5]
        ],
        "aio": (data.get("ai_overview") or {}).get("text", "")[:400],
        "paa": [q.get("question", "") for q in data.get("people_also_ask", [])[:3]],
    }

def run():
    date = datetime.utcnow().strftime("%Y-%m-%d")
    context_dir = Path("agent_context")
    context_dir.mkdir(exist_ok=True)

    results = [fetch_and_compress(q) for q in AGENT_QUERIES]
    context = {
        "fetched_at": datetime.utcnow().isoformat(),
        "date": date,
        "queries": len(results),
        "data": results,
    }

    context_path = context_dir / "latest.json"
    context_path.write_text(json.dumps(context, indent=2))
    # Also archive by date
    (context_dir / f"context_{date}.json").write_text(json.dumps(context, indent=2))

    total_chars = sum(len(json.dumps(r)) for r in results)
    print(f"Agent context bridge {date}: {len(results)} queries, {total_chars:,} chars total")
    for r in results:
        print(f"  {r['q'][:50]}: {len(r['organic'])} results, AIO={'yes' if r['aio'] else 'no'}")

if __name__ == "__main__":
    run()

const API_KEY = "your_scavio_api_key";
const QUERIES = ["best search API for AI agents 2026", "web search API pricing comparison", "MCP search tool integration"];

async function fetchAndCompress(query) {
  const res = await fetch("https://api.scavio.dev/api/v1/search", {
    method: "POST",
    headers: { "x-api-key": API_KEY, "content-type": "application/json" },
    body: JSON.stringify({ platform: "google", query, ai_overview: true }),
  });
  if (!res.ok) throw new Error(`scavio ${res.status}`);
  const data = await res.json();
  return {
    q: query,
    organic: (data.organic ?? []).slice(0, 5).map((r) => ({ t: (r.title ?? "").slice(0, 80), s: (r.snippet ?? "").slice(0, 150), u: r.link ?? "" })),
    aio: ((data.ai_overview ?? {}).text ?? "").slice(0, 400),
    paa: (data.people_also_ask ?? []).slice(0, 3).map((q) => q.question ?? ""),
  };
}

const results = [];
for (const q of QUERIES) results.push(await fetchAndCompress(q));
const totalChars = results.reduce((s, r) => s + JSON.stringify(r).length, 0);
console.log(`Agent context: ${results.length} queries, ${totalChars.toLocaleString()} chars`);