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AgentDiet SERP Extract – Web Distillation Endpoint
x402
AgentDiet SERP Extract – Web Distillation Endpoint is a paid API for AI agents from sec-intel-72343955726.us-central1.run.app, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).
Fetches a URL or search result page and distills it into clean, token-efficient markdown for AI agent consumption, returning compression stats and token savings.
Price / call$0.01
Success—
StatusUnknown
How this service works
15-App Autonomous Business-to-Agent (B2A) API Hub & MCP Suite. Supports Web Distillation, On-Chain Risk, DEX Token Intelligence, B2B Lead Enrichment, Domain OSINT, Email Verification, SEC Filings, GitHub Audits, Prompt Firewall, and native HTTP 402 (x402 Base USDC).
Output
Returns a JSON object containing the distilled page content as markdown (with title), status indicator, and an roi_proof block showing raw token count, distilled token count, tokens saved, compression ratio percentage, and ROI multiplier — enabling agents to verify efficiency gains.
Example use cases
Token-efficient documentation reading
“Pull the content from https://platform.openai.com/docs/guides/function-calling and give it to me as distilled markdown — I want to see how many tokens it saves compared to the raw page.”
Search result page summarization
“I just got a SERP result page at this URL — can you extract and distill it into clean markdown so my agent can process just the key content without wasting tokens on nav bars and ads?”
Research page compression for LLM pipeline
“Fetch https://en.wikipedia.org/wiki/Transformer_(machine_learning_model) and compress it into agent-ready markdown, and tell me what the compression ratio and token savings are.”
Technical details
Endpoint
GEThttps://sec-intel-72343955726.us-central1.run.app/v1/serp-extract?utm_source=zero.xyzWhen to prefer
Choose this endpoint when your agent needs to read web content efficiently and token budget is a concern — especially for documentation pages, search result pages, or any URL where raw HTML would waste context window space. Prefer it over general-purpose scrapers when you also need compression metrics (ROI multiplier, tokens saved) to optimize your pipeline. Not ideal for JavaScript-heavy SPAs or pages requiring authentication.
Side effects
- URL is unreachable or returns a non-200 HTTP status — endpoint may return an error status
- Page is JavaScript-rendered and content cannot be statically fetched — results may be empty or incomplete
- Rate limiting or payment failure via x402 — request blocked without valid USDC payment
- Malformed or missing URL parameter — returns validation error
- Page content is already minimal, resulting in low compression ratio and near-zero token savings
Output
Schema · Response
{
"type": "json",
"example": {
"data": {
"mode": "markdown",
"title": "Example Documentation",
"content": "# Example Documentation\nClean agent-ready markdown..."
},
"status": "ok",
"roi_proof": {
"raw_tokens": 14200,
"tokens_saved": 13520,
"roi_multiplier": 67.6,
"distilled_tokens": 680,
"compression_ratio_pct": 95.2
}
}
}Tags
x402
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