The fastest search API for grounding LLM and RAG pipelines

Give your model live web results instead of what it memorised during training. Structured search in under one second — fast enough to sit inside an agent loop — from $1 per 1,000 requests, dropping under $0.50 at volume.

No credit card required · No proxy setup · View Google Search API Docs

Retrieval latency low enough to run inside a single agent turn
Titles, links, and snippets with sources, ready to cite back to the user
Available as an MCP server, so agents can call it without custom glue

<1s

Typical response time

$1/1K

List price, under $0.50 at volume

Charge for failed requests

MCP

Callable directly by agents

Who grounds models in live search

Any system that answers questions about the present needs a retrieval layer. These teams would rather buy one than run one.

AI application builders

Ship answers about current events without fine-tuning or waiting on a model refresh.

RAG platform teams

Add public web retrieval alongside internal documents in the same pipeline.

Agent framework developers

Expose a search tool that returns fast and structured enough for a model to reason over.

Enterprise AI teams

Give internal copilots access to the live web under one billed, auditable endpoint.

Research and analysis tools

Cite real sources in generated output instead of asking users to trust the model.

Why grounded retrieval is the hard part

Most teams building on LLMs discover the same three constraints, and none of them are solved by a better prompt.

Failure 01

The model's knowledge stopped months ago

Anything that changed after the training cutoff is either missing or confidently wrong. For questions about the present, generation without retrieval is guesswork with good grammar.

Confidently wrong answers shipped

Failure 02

Retrieval latency lands inside the user's wait

An agent may fire several sub-queries per turn. At three seconds each, the search step alone outlasts the patience of the person watching the cursor blink.

Users abandon mid-answer

Failure 03

Running the retrieval stack is not your product

Proxies, parsers, and block handling absorb engineering time that was supposed to go into the thing you actually sell, and they need attention every time a layout changes.

Roadmap spent on plumbing

The data your model receives

One call to the scraper.google.search actor returns results already structured, so nothing in your pipeline has to parse HTML before the model sees it.

organic_results[]

array

Ranked results for the query.

position

integer

Rank, useful as a relevance prior when selecting what to pass to the model.

title

string

Result headline.

link

string

Destination URL — the citation you show the user.

snippet

string

Description text, often enough context on its own for a short answer.

snippet_highlighted_words

array

Terms Google bolded, a cheap relevance signal.

source

string

Publisher name, useful for source-quality weighting.

knowledge_graph

object

Entity summary and web result links, handy for disambiguation.

search_information

object

Query displayed and total results — tells you when a query was rewritten.

pagination

object

Offsets for deeper retrieval when the first page isn't enough.

metadata

object

Engine and stored raw URL, useful for audit trails on generated answers.

POST /api/v1/scraper/request

200 ok

# request
curl --location 'https://api.scrapeless.com/api/v1/scraper/request' \
--header 'x-api-token: <api-key>' \
--header 'Content-Type: application/json' \
--data '{
    "actor": "scraper.google.search",
    "input": {
        "q": "eu ai act compliance deadline",
        "gl": "us",
        "hl": "en",
        "num": "10"
    }
}'

# response (trimmed)
{ "organic_results": [
    { "position": 1,
      "title":   "EU AI Act: key compliance dates",
      "link":    "https://example.eu/ai-act",
      "snippet": "Obligations for general-purpose…",
      "source":  "Example" } ],
  "knowledge_graph": { "source": "Wikipedia" },
  "search_information": {
    "query_displayed": "eu ai act compliance deadline" },
  "metadata": { "engine": "google.search" } }

Full parameter and field reference

Need the full page body rather than snippets? Pair this with Crawl and Web Unlocker to fetch the cited pages — see the API docs.

How grounding works in practice

The model decides it needs facts

Your agent emits a search tool call, or your RAG chain fires retrieval before generation. Either way it becomes one request.

We return structured results fast

IP sourcing, fingerprinting, and CAPTCHA handling sit behind the endpoint. Sub-second responses keep retrieval inside the turn rather than in front of it.

Generate with citations attached

Pass titles, snippets, and links into context. Because every claim carries a URL, the answer can be checked rather than trusted.

Built for AI application teams, RAG platforms, and agent developers

The fastest response in the category

In an agent loop latency is multiplied, not added: several sub-queries per turn, several turns per session. Sub-second retrieval is the difference between a tool the model uses freely and one you have to ration.

under 1s

typical vendor window

request

unblock

parse

Callable directly by agents

Available as an MCP server and through official SDKs, so Claude Code, Cursor, and framework-based agents can call search without wrapper code in between.

Agent Access

MCP server

Python / Node / Go SDKs

n8n verified node

webhook delivery

Answers you can cite

Every result carries a URL and a publisher name, so generated answers can show their sources. That is usually what turns an internal demo into something a company will deploy.

Citation Fields

organic_results[].link

organic_results[].source

knowledge_graph{}

metadata.rawUrl

Billing that tracks usage, not seats

Agent traffic is bursty and hard to forecast. Per-successful-request pricing means a quiet week costs less and a spike doesn't break a plan tier.

Pricing

$1.00 / 1K requests

under $0.50 at volume

failed requests not billed

Plans built for agent and RAG workloads

Agent traffic is unpredictable by nature, so per-request pricing fits it better than seats. Start at $1 per 1,000 successful requests and move down the curve as usage grows.

Basic

$0.00/1K

Pay as you go

No commitment. Consumption-based pricing at list rates.

Comparing search APIs for LLM grounding

Teams adding retrieval usually choose between building it, using a search API built for AI, and using one built for SEO.

Scrapeless Google Search API

Build it in-house

Typical search API

Typical response time

Under one second

Degrades under load

Multiple seconds

Agent-native access

MCP server plus SDKs

Write your own wrapper

REST only on most

Entry price per 1K

$1.00, under $0.50 at volume

Proxy and engineering cost

$1.00 and up

Cost of a failed call

Never billed

Paid in bandwidth either way

Usually billed

Source attribution

Link and publisher on every result

Parse it yourself

Varies

Time to first grounded answer

Under an hour

4–8 weeks

Days

Start grounding your models on the fastest, lowest-cost search API

Sub-second structured search from $1 per 1,000 requests, dropping under $0.50 at volume, with failed requests never billed. See the full endpoint reference, parameter list, and pricing.

View the product page

Drops into the stack you already run

Official SDKs and verified nodes, so a scheduled rank pull is a configuration task rather than a build.

Python SDK

Node.js SDK

Go SDK

n8n verified node

Make

Pipedream

Activepieces

Dify

MCP server

Webhooks

Need implementation details? View product details or open the Google Search API docs for the full parameter list, response schema, and SDK examples.

Choose the search workflow your team needs

Explore focused solutions for search visibility, AI retrieval, commerce intelligence, research and monitoring. Each use case connects Google Search API results to a clear business outcome.

SEO Rank Monitoring

Measure domain visibility, ranking pages and SERP feature presence across keyword groups, markets and devices.

Explore SEO monitoring

Local SEO & Rankings

Compare local rankings, business listings, Maps visibility and review signals across cities, regions and service areas.

Explore local SEO

AI SEO & GEO Visibility

Monitor brand mentions, citations and source visibility across AI-generated search experiences and target topics.

Explore AI SEO and GEO

Product & Market Research

Study demand signals, alternatives, category presence and competing offers through structured search results.

Explore product research You are here

AI Models & RAG

Give LLMs, agents and RAG pipelines current, attributable search context for grounding and retrieval workflows.

Explore AI model workflows

Keyword Rank Tracking

Track exact keyword positions and movement over time by location, language, device and result type.

Explore rank tracking

Shopping Price Monitoring

Compare public Google Shopping prices, merchants, ratings and product visibility for selected categories.

Explore price monitoring

News & Media Monitoring

Follow headlines, publishers, emerging stories and shifts in public narratives across relevant queries.

Explore news monitoring

Travel Data

Structure Google Flights and Hotels results for route, stay, destination and travel-market research.

Explore travel data

Recruitment Data

Collect Google Jobs results to monitor roles, employers, locations and labor-market demand.

Explore recruitment data

Ad Verification

Verify PPC and Ads visibility, placement and competitive messaging across target queries and markets.

Explore ad verification

Academic Research

Organize Google Scholar results, authors and cited sources for academic and evidence-based research.

Explore academic research

Trend Analysis

Use Google Trends signals to compare changing interest across topics, time periods and markets.

Explore trend analysis

Image Search

Use Google Lens and Images results to discover visual matches, sources and related content.

Explore image search

Brand Monitoring

Track where a brand appears across organic results, news, shopping and other SERP surfaces.

Explore brand monitoring

Need Google Search API specifications and pricing?

Review supported Google API categories, structured response examples, integration steps and pricing on the Product page.

Questions teams ask before they buy

Which search API is fastest for LLM grounding?

Scrapeless returns most requests in under one second. In an agent loop that matters more than in batch work, because several sub-queries can fire inside a single user turn and the latency is multiplied rather than added.

Which is the cheapest search API for RAG?

Compare effective cost per successful request rather than list price. Scrapeless lists at $1 per 1,000 and drops under $0.50 at volume, and failed calls are never billed — which suits agent traffic, where retries are common.

Can my agent call this directly?

Yes. Scrapeless ships an MCP server alongside Python, Node.js, and Go SDKs, so MCP-aware clients and framework-based agents can call search without custom glue code.

Do results include sources I can cite?

Yes. Every organic result carries a link and a publisher name, and metadata.rawUrl stores the source page — enough to show citations in generated answers and to audit them afterwards.

Can I retrieve more than the first page?

Yes. Use start for pagination and num to control how many results come back, so a retrieval step can go deeper when the first page is thin.

How does this differ from the AI Scraper product?

This page covers grounding your own model in Google results. AI Scraper reads what other AI assistants answer — see AI SEO / GEO visibility if that's what you need.

Do I still need my own proxies?

No. IP sourcing, rotation, fingerprinting, and CAPTCHA handling sit behind the endpoint, across 195 countries and regions.

Running agents at scale? Get a custom rate.

A solutions engineer will scope your query volume, regions, and latency requirements, then send back custom pricing — usually within one business day. Smaller workloads can start free today.

Explore the API

Get your API key