# Web Data API for AI Agents — MCP Native

> MCP-native web data API for AI: search, scrape, crawl and map as agent tools, one JSON envelope, schema-valid extraction, pay per success. $1 free monthly.

[Home](https://quanticdata.io/)/*Web Data API for AI*

# Web data API for AI — your agent drives it

Web data for AI is web content collected and shaped so models can use it directly: clean Markdown, stable JSON, verifiable sources. QuanticData exposes search, scraping and crawling as native MCP tools over four proxy networks, bills only successful calls, and starts at $0.0002 per page.

[Get my free API key](https://quanticdata.io/signup/) [See the MCP tools](/web-data-api-for-ai/#mcp)

$1 free every month · No card required · Pay per success

mcp · agent session

```
# the agent decides every call itself
tool call · search
  { "query": "rtx 5090 restock eu", "engine": "google" }
→ organic[10] · people_also_ask[4] · ai_overview
tool call · scrape
  { "url": "https://nova-tech.de/rtx-5090" }
→ "# RTX 5090 — €1,899 · in stock"
→ usage: { "cost_usd": 0.0002 }
```

7 tools, one key *search* *scrape* *crawl* *map* *batch* *seo_audit* *crawl_status*

**MCP built in**search · scrape · crawl · map · batch · seo_audit

**One JSON envelope**same shape across every product

**4 proxy networks under it**residential · mobile · datacenter · IPv6

**Pay per success**agents retry free — failures cost nothing

Pricing

## Priced for exploratory agents

Agents probe, retry and dead-end by design — so failed calls are never billed, and every response tells the agent what it just spent.

**$0.0002**per page scraped*$0.001 with JS rendering*

**$0.0005**per SERP search*$0.002 with JS rendering*

**$0.0003**per crawled page*async, auto-refund on unused*

**$0.0002**per batch URL*up to 1,000 URLs per job*

### Pay as you go

$0/mo

- $1 free credit / month

- 60 requests / min

- List unit prices

### Starter

$19/mo

- $10 free credit / month

- 300 requests / min

- 10% off unit prices

Most popular

### Growth

$79/mo

- $50 free credit / month

- 600 requests / min

- 20% off unit prices

### Scale

$299/mo

- $250 free credit / month

- 1,200 requests / min

- 30% off unit prices

Usage cost in every responseFailed calls never billedAsync jobs auto-refund failuresOne key for APIs and proxiesLLM-ready Markdown

## What is web data for AI?

**Web data for AI is web content collected, cleaned and structured so language models can consume it directly** — as grounding for answers, context for RAG, or corpora for training. The difference from classic scraping is the consumer: a model needs token-efficient text, stable schemas and provenance, not raw HTML.

QuanticData was built for that consumer. Every page comes back as clean Markdown with metadata for citations; every search as stable, SerpApi-compatible JSON; every product through **one envelope an agent learns once** — and the whole surface is callable by the agent itself, not just by your backend.

Provenance included title · author · publish date · canonical URL on every page — citations come free with the content

## Your agent holds the tools

The [QuanticData MCP server](https://quanticdata.io/mcp-server/) turns the whole platform into a toolbox the model calls on its own: `search` across three engines and 17 verticals, `scrape` with structured or AI extraction, `crawl` and `map` for whole sites, `batch` for lists, `seo_audit` for rendering diffs. Typed schemas, so the model knows what each tool takes and returns.

Connect it once from your dashboard to Claude, Cursor or any MCP-capable client — **no glue code, no SDK, no per-framework adapters**. Async jobs poll incrementally with cursors, so long crawls don't blow the context window. Prefer REST? The same tools are plain HTTP endpoints with the same envelope.

acme-store.com/gpus

1. goto acme-store.com/gpus

2. click “In stock only”

3. extract 24 products

4. { "products": [ … ] } · schema valid

## From live web to model-ready data

### Agent grounding

Give assistants live answers with sources: a search tool for discovery, a scrape tool for depth, cost visibility on every call.

### RAG ingestion

Markdown chunks with GFM tables, canonical URLs and publish dates — your embedder and your citations fed by the same response.

### Corpus building

Map a site's URLs, crawl it breadth-first, batch-refresh what changed. Unused crawl pages are refunded automatically.

### Structured extraction

Describe fields in a schema — or in plain language — and get schema-valid JSON out, ready for downstream functions.

### SERP intelligence

Rankings, People Also Ask and AI Overviews as stable JSON — the raw material for SEO agents and market monitors.

### Hard targets

Four proxy networks and browser escalation under the same API — when a source fights back, the agent doesn't need to know.

### Four networks under the hood — yours too, if you want them

Every call routes through QuanticData's own residential, mobile, datacenter and IPv6 networks. Need raw transport instead of finished data? The same networks are sold as [plain proxies](https://quanticdata.io/residential-proxies/) under the same account.

[See the proxy networks](https://quanticdata.io/#l-connection)

Integration

## REST when you drive, MCP when the agent does

```
curl https://api.quanticdata.io/v1/scrape \
  -H "Authorization: Bearer $QD_API_KEY" \
  -d '{ "url": "https://acme.dev/blog/chunking",
        "format": "markdown", "contentMode": "article" }'
```

```
import requests

r = requests.post("https://api.quanticdata.io/v1/scrape",
    headers={"Authorization": f"Bearer {KEY}"},
    json={"url": "https://acme.dev/blog/chunking",
          "format": "markdown", "contentMode": "article"})

doc = r.json()["data"]          # feed your RAG pipeline
chunks = split(doc["content"])  # citations: doc["metadata"]
```

```
const r = await fetch("https://api.quanticdata.io/v1/scrape", {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.QD_API_KEY}` },
  body: JSON.stringify({ url: "https://acme.dev/blog/chunking",
    format: "markdown", contentMode: "article" })
});
const { data } = await r.json(); // data.content → your embedder
```

## Works where your agent lives

MCP-capable environments connect natively; everything else wraps one HTTP endpoint as a custom tool in a few lines. The response envelope never changes between them — prototype in Claude, ship in LangChain, monitor from n8n, same fields throughout. Just need one piece? The [SERP API](https://quanticdata.io/serp-api/) and the [web scraping API](https://quanticdata.io/web-scraping-api/) stand alone too.

Chips, not lock-in *Claude* *Cursor* *n8n* *LangChain* *CrewAI* *OpenAI Agents SDK* *LlamaIndex* *Zapier*

## QuanticData vs a typical AI data tool

|  | QuanticData | Typical AI data tool |
| --- | --- | --- |
| Entry price | $0 — pure pay-as-you-go | monthly plan with credit bundles |
| Failed calls | never billed, refunded in async jobs | consume credits |
| Cost visibility | usage block in every response | dashboard only |
| Output | one envelope across search, scrape, crawl | per-product schemas |
| Network | 4 in-house proxy networks, also sold raw | opaque, API-only |
| Free tier | $1 every month, renews forever | one-time trial credits |

## FAQ

The short answers on pricing, formats and setup.

[Something else? Ask us →](mailto:hello@quanticdata.io)

### Why do AI agents need a dedicated web data API?

Because agents consume the web differently than humans or scrapers do. They need tools they can call on their own, content that doesn't waste tokens on nav and markup, stable field names they can rely on across calls, and billing that doesn't punish exploratory requests. A generic scraper solves none of that by default.

### What is MCP (Model Context Protocol)?

MCP is an open standard that lets AI assistants connect to external tools and data sources. A server declares tools with typed schemas; the model decides when to call them. Claude, Cursor and a growing set of frameworks speak it natively — connect a server once and the agent gains those capabilities.

### Which MCP tools does QuanticData expose?

Seven: search (every engine and vertical), scrape (single pages with optional structured or AI extraction), crawl and crawl_status (whole-site jobs), map (URL discovery), batch and batch_status (up to 1,000 URLs per job), plus seo_audit for comparing a page's no-JS and rendered views.

### How does pay-per-success billing work?

A call is charged only when it returns a usable result — blocked pages, captchas, timeouts and internal retries cost nothing. That matters for agents in particular: they explore, retry and dead-end by design, and each response carries a usage block so the agent can see what a call actually cost.

### Can I use it for RAG pipelines?

Yes — that is the primary shape of the output. Pages arrive as clean Markdown with GFM tables, absolutized links and metadata (title, author, publish date, canonical) for citations. Map discovers a site's URLs, crawl fetches them, and batch keeps a corpus refreshed on your schedule.

### Can I use it to collect LLM training data?

Yes. The same APIs scale from single pages to site-wide crawls, routed through four proxy networks for geographically diverse collection. You are responsible for the usual diligence on sources — licensing, robots directives, personal data — the API gives you the collection layer, not the legal cover.

### What format do responses come in?

One JSON envelope across every product, so an agent learns the shape once. Page content is Markdown, HTML or text; SERP results use SerpApi-compatible fields; structured extraction returns exactly the fields your schema names; and each billed response includes a usage block with its cost.

### Which agent frameworks does it work with?

MCP-capable environments — Claude, Cursor and others — connect natively. Everything else integrates over plain REST with one endpoint per tool: LangChain, CrewAI, LlamaIndex and the OpenAI Agents SDK wrap it as a custom tool in a few lines, and n8n or Zapier call it from an HTTP node.

### How much does it cost?

List prices: $0.0002 per scraped page ($0.001 with JS rendering), $0.0005 per search ($0.002 rendered), $0.0003 per crawled page, $0.0002 per batch URL. No subscription or monthly minimum; optional tiers from $19 to $299 per month add free credit, higher rate limits and up to 30% off.

### Is there a free tier?

Yes. Every account gets $1 of free usage each month with no card required — thousands of scrapes or searches, renewed monthly, shared across all Data APIs. It is enough to wire the MCP server into your agent and run real workloads before deciding to pay anything.

### How is this different from using proxies directly?

Proxies give you transport: an IP in the right country and nothing else — fetching, rendering, parsing and retries stay your problem. The Data APIs sit on top of the same four networks and hand back finished data. Use whichever layer fits; both live under one account and one key.

### Is collecting web data for AI legal?

Collecting publicly accessible web data is generally lawful in most jurisdictions, but copyright, site terms and privacy law still apply — and AI training adds active regulatory debate on top. Collect public content, respect the target's terms, mind personal data, and get legal advice for your specific use case.

## Give your agent the web

$1 free every month, no card. Connect the MCP server and let it work.

[Get my free API key](https://quanticdata.io/signup/)

Also on the platform: [AI Web Scraping Service](https://quanticdata.io/ai-web-scraping-service/) [Market Research Data](https://quanticdata.io/market-research-data/) [Web Scraping API](https://quanticdata.io/web-scraping-api/) [SERP API](https://quanticdata.io/serp-api/) [Residential Proxies](https://quanticdata.io/residential-proxies/) [Mobile Proxies](https://quanticdata.io/mobile-proxies/) [Datacenter Proxies](https://quanticdata.io/datacenter-proxies/) [ISP Proxies](https://quanticdata.io/isp-proxies/) [Rotating Proxies](https://quanticdata.io/rotating-proxies/) [Sneaker Proxies](https://quanticdata.io/sneaker-proxies/) [SOCKS5 Proxies](https://quanticdata.io/socks5-proxies/) [IPv6 Proxies](https://quanticdata.io/ipv6-proxies/)

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Source: https://quanticdata.io/web-data-api-for-ai/ · Site index for AI: https://quanticdata.io/llms.txt