# Scraping Agency

> Managed, monitored web data feeds for teams and AI agents. Built by AI agents, checked by engineers, delivered by API, MCP or file, with the source on every row.

Scraping Agency builds and runs managed web data feeds, website monitoring, custom datasets (including AI training, eval and RAG data) and agent-ready delivery (hosted MCP servers and APIs). AI agents write and repair the extractors, deterministic code runs them, a QA gate with cross-model checks decides what ships, and every value carries its source URL and retrieval timestamp. Prices are public and in USD.

## Services
- [Managed data feeds](https://scrapingagency.com/managed-data-feeds/): Scheduled, monitored feeds from any public source.
- [Web monitoring](https://scrapingagency.com/web-monitoring/): Track competitor and market pages, get the change.
- [Custom datasets](https://scrapingagency.com/custom-datasets/): One-off research datasets and AI training / eval data.
- [Agent-ready data](https://scrapingagency.com/agent-ready-data/): Your data as an MCP server or API for your agents.
- [Company enrichment](https://scrapingagency.com/data-enrichment/): Company records filled in from public sources.

## Pricing
- Single feed: $600 per source / month. One source, refreshed weekly. Daily refresh with an SLA from $1,000.
- Team: $3,000 per month. Up to 5 sources, daily refresh, monitoring included.
- Scale: $6,000+ per month. Many sources, high volume or hourly data. Quoted per project.
- Data Sprint: from $1,500. A custom one-off dataset with its source list and a short method note.
- Monitoring: from $400 / month. A watchlist of 25 pages: changes, diffs and plain-language summaries.
- Feasibility check: $950. Can it be collected reliably, how, and at what running cost. Credited against setup.
- AI datasets: $5k–30k. Eval sets, RAG corpora and fine-tuning data with full provenance. Quoted.
- Free 100-row sample within 2 business days: https://scrapingagency.com/contact/

## Company
- [How it works](https://scrapingagency.com/how-it-works/)
- [Pricing](https://scrapingagency.com/pricing/)
- [Case study](https://scrapingagency.com/case-studies/nomad-watch/)
- [About](https://scrapingagency.com/about/)
- [Contact](https://scrapingagency.com/contact/)

## Research
- [AI Crawler Access Index](https://scrapingagency.com/research/ai-crawler-access-index/): How the top 1,000 sites treat AI bots.

## Guides
- [Can your AI agent replace a web scraping service?](https://scrapingagency.com/guides/can-ai-agents-replace-web-scraping/): For one-off, small or exploratory jobs, yes: a browser agent or an MCP scraping tool will get you a few hundred rows for the price of a subscription. For recurring feeds, high volume, monitoring, a stable schema or heavily protected sites, no: agents still finish only about 30–60% of real-web tasks in independent tests and cost far more per page than code.
- [Cloudflare's 2026 AI bot rules, explained for data teams](https://scrapingagency.com/guides/cloudflare-ai-bot-rules-2026/): Since July 2025 Cloudflare has blocked AI crawlers by default on new domains, added Pay Per Crawl, Content Signals and signed agents (Web Bot Auth), and in July 2026 split bots into Search, Agent and Training. From 15 September 2026, new domains block Agent and Training bots by default on pages that show ads. Expect more 403s and challenges, and plan for identified, signed or paid access.
- [Web data for AI agents: managed feeds vs. live browsing vs. search APIs](https://scrapingagency.com/guides/web-data-for-ai-agents/): Live browsing suits one-off actions on a page, search and extract APIs suit open-ended questions across the long tail, and managed feeds suit the core data your agent queries every day and must trust. Most production agents need a pre-collected, structured feed for the core entities, a search API for everything else, and live browsing only as a last resort.
- [Browser agents vs. scrapers: cost per page, success rates and failure modes](https://scrapingagency.com/guides/browser-agents-vs-scrapers/): Conventional scrapers cost around a tenth of a cent per page through an API and fail loudly when a site changes. Browser agents cost roughly $0.02–0.50 per task, finish about 30–61% of real-web tasks in independent tests, and fail quietly. Use agents to explore sites and to write and repair scrapers. Use scrapers to run anything recurring.
- [How to monitor competitor prices at scale](https://scrapingagency.com/guides/competitor-price-monitoring/): Competitor price monitoring at scale is mostly a matching and QA problem, not a scraping problem. Match products on identifiers such as GTIN and MPN before titles, set refresh cadence by SKU tier, capture price with currency, region, variant and stock status, alert only on re-checked changes, and keep a source URL and timestamp on every observation.
- [How to give your AI agent reliable web data with MCP](https://scrapingagency.com/guides/mcp-server-for-web-data/): Give an agent reliable web data by exposing narrow MCP tools with typed input and output schemas, and by returning a source URL and retrieval timestamp with every value. Use live-scrape tools for open-ended, one-off lookups; use curated-dataset tools when the agent needs the same entities repeatedly and has to trust the answer.
- [What a data provenance record should contain](https://scrapingagency.com/guides/data-provenance-checklist/): A useful provenance record lets anyone answer where a value came from, when it was observed, how it was extracted, and how much to trust it. At minimum: source URL, retrieved_at, collection method, extractor version, a confidence or review status, whether the value is observed, derived or estimated, and an append-only change history.
- [Building eval and RAG datasets from web data](https://scrapingagency.com/guides/eval-and-rag-datasets-from-web-data/): The big money in AI training data goes to expert human data firms and licensed content deals, not to raw web scraping. Web data earns its place in narrower jobs: niche and multilingual corpora, eval sets with sourced answer keys, and RAG knowledge feeds that stay fresh. Quality there depends on dedup, contamination checks, and per-document source, date and access-signal metadata.

## Comparisons
- [Managed data feed vs. a DIY AI agent: which one fits your web data job](https://scrapingagency.com/compare/managed-feed-vs-diy-agent/): A DIY AI agent is the better choice for one-off lists, research and small or occasional pulls: it is fast and often already included in a subscription. A managed feed earns its cost when the same data has to arrive on schedule, in a fixed schema, with monitoring and a source for every value, week after week.
- [Apify, Bright Data, Zyte, Firecrawl or a managed service: who each is for](https://scrapingagency.com/compare/scraping-apis-and-platforms/): Apify is a marketplace of ready-made scrapers, Bright Data sells proxies, unblocking and prebuilt datasets, Zyte sells a difficulty-priced unblocking API, and Firecrawl turns pages into LLM-ready markdown. All four sell access and tooling; you still own the pipeline. A managed service makes sense when you want the outcome, a monitored feed, rather than the tools.
- [ScrapeHero, Grepsr and PromptCloud alternatives: choosing a managed scraping service](https://scrapingagency.com/compare/managed-scraping-services/): ScrapeHero, Grepsr and PromptCloud are established managed scraping firms, each reporting more than a decade in business; ScrapeHero publishes prices from $199 per site per month, Grepsr from $100 for one-off jobs, and PromptCloud quotes per project. Whichever you consider, judge them on SLA terms, fix times, schema versioning, monitoring, provenance, pricing transparency and exit terms.

Contact: rutger@scrapingagency.com