Context.dev: The Web Data API Your Agents Call When They Need to Read the Internet
Every AI product eventually needs the same unglamorous capability: read a web page reliably, turn it into clean data, and do it again tomorrow when the page changes. Teams either build that crawler-proxy-parser stack themselves and maintain it forever, or they buy it as an API. Context.dev is the buy option, web data as a service, shaped for the AI-agent era.
The short version
Context.dev is a web data API platform: scrape any URL into Markdown or HTML, crawl whole sites, parse documents, extract structured data against a JSON schema you define, and monitor pages with webhook alerts when they change. It is SOC 2 certified, Y Combinator backed, used by real developer-tool companies, and priced from a genuinely free tier through affordable developer plans, so the build-versus-buy math is easy to run.
The capability menu
Scraping returns pages as clean Markdown or HTML with the boilerplate gone, the format LLM pipelines want. Crawling walks entire sites for knowledge-base ingestion. Structured extraction is the power feature: hand it a JSON schema and a URL, get back typed data pulled from the page, no brittle selectors to maintain. Monitoring closes the loop, watch pages and receive webhooks on change, so your data stays current without a cron job full of hope. Brand intelligence and industry classification endpoints round out the set for enrichment use cases.
Built for agents, priced for developers
The design assumption is that your caller might be an AI agent: clean data shapes, SDKs in the common languages, credits that map to operations. Pricing starts free, 500 credits with a work email, with the Developer tier at 25 dollars a month for 10,000 credits and higher tiers scaling to the millions, annual billing takes two months off. For RAG products, research agents, monitoring tools and enrichment pipelines, that is infrastructure at side-project prices.
Before you integrate
Credit budgeting is the real design work, crawl once and monitor for changes beats re-crawling nightly, and the difference is your bill. The hardest anti-bot fortresses resist every scraping vendor, plan around the small percentage of targets that fight back. Otherwise the integration is deliberately boring: key, endpoint, clean data.
Where it shines
- Scrape, crawl, extract and monitor in one API
- Schema-based extraction, no selector upkeep
- Webhook monitoring keeps data fresh
- SOC 2, YC-backed, real customers
- Free tier and a 25 dollar developer plan
Worth knowing
- Credit math needs a refresh strategy
- Hardened sites resist all vendors
- Chunking and pipeline design stay yours
Common questions
How is this different from other scraping APIs?
The breadth in one surface, page scraping plus site crawling plus schema extraction plus change monitoring, most rivals make you compose two or three products to cover that.
What does the free tier include?
500 credits with a work email signup, 250 otherwise, enough to prototype a real integration before any payment conversation.
Can it feed a RAG pipeline directly?
Yes, crawl output arrives as clean Markdown per page, ready for chunking and embedding, that ingestion loop is one of its primary use cases.
Bottom line
If your product needs to read the web and you are tempted to build the scraper stack yourself, run the Context.dev free tier first, one afternoon usually settles the build-versus-buy question in favor of shipping your actual product.