REST API Y-Combinator Context Engineering Platforms Web Scraping AI-Powered Web Crawling

Value Proposition & Features

Context.dev provides a managed web-data API for AI agents and LLM pipelines: it retrieves web pages, renders JavaScript, crawls sites, and returns LLM-ready Markdown or structured JSON through one interface. [rbz9lm] It also supports browser actions, MCP, REST APIs, and SDK-based integrations for applications and data pipelines. [l0qenp]
  • Scraping: Returns Markdown , HTML , images, screenshots, or JSON from a URL. [6gkbf3]
  • JavaScript rendering: Handles dynamic pages without requiring users to operate their own browser infrastructure. [6gkbf3]
  • Browser actions: Supports ordered click, type, wait, and scroll operations on rendered pages. [l0qenp]
  • Crawling: Synchronously crawls up to 500 pages with controls for page count, depth, paths, and time limits. [6gkbf3]
  • Structured extraction: Accepts JSON Schema and returns schema-shaped data; successful JSON extraction adds four credits. [6gkbf3]
  • Research answers: The Answers API returns structured JSON with source URLs; Fast mode costs 10 credits and Ultra mode costs 100 credits. [rbz9lm]
  • Agent connectivity: Supports MCP with OAuth alongside REST APIs and SDKs . [l0qenp]
  • Additional data tools: The product surface includes search, sitemaps, PDF parsing, brand enrichment, batches, monitors, and Webhooks . [6gkbf3]

Screenshots

No three official product screenshots were identified in the available search results.

Product Roadmap / Announcements

As of October 10, 2026,
  • September 28, 2026 — Context Highlights: Context.dev announced a feature that returns passages relevant to a webpage query, reducing the number of tokens an agent must process. [zbi1gh]
  • September 16, 2026 — Answers API: Context.dev introduced an API that converts a question or research task into structured JSON with source URLs. [rbz9lm]

Recent Developments

  • Context.dev published documentation and examples for MCP , browser agents, production scraping pipelines, and web-scraping integrations during September and October 2026. [l0qenp] [f3hogg] [5n8034]
  • Its October 2026 pricing guidance describes a free plan with 1,000 monthly credits for work-email accounts or a one-time 250-credit allowance for personal-email accounts. [6gkbf3]

History and Origin Story

Context.dev was founded in 2025 and is associated with Y Combinator ’s Summer 2026 batch. [E1] Its public product direction has expanded from URL scraping and crawling toward agent-oriented research, structured answers, MCP connectivity, and context-reduction tools such as Context Highlights. [rbz9lm] [zbi1gh]

Fundraising History

Round Date Amount Lead investor
Y Combinator S26 2026 No reliable amount found Y Combinator
Total — No reliable total found —
Y Combinator

Notable Team Members

No reliable public search result identified the founders or other notable team members. The supplied company material reports a workforce of six, but does not name its members. [E1]

Market Sizing

Category, Market Size, and Category Growth

Context.dev operates in the managed web-scraping, web-crawling, structured-data extraction, and AI-agent data infrastructure categories. Its positioning specifically targets applications that need live web context delivered as Markdown, rendered content, structured JSON, or research answers. [rbz9lm] [6gkbf3]
No reliable analyst-firm or financial-journalism estimate for Context.dev’s addressable market or category growth was found in the available search results.

Pricing

Tier Published price Included credits
Free — work email $0 1,000 monthly
Free — personal email $0 250 one-time
Developer $19/month 7,500
Pro $99/month 125,000
Growth $299/month 500,000
Scale $499/month 1,000,000
The published pricing describes annual billing as saving two months and offers optional automatic top-ups on paid plans. [6gkbf3] Standard scraping starts at one credit per page, or two credits with browser actions; successful JSON extraction adds four credits. [6gkbf3]

Revenue Trajectory Estimates

No reported or reliable estimated revenue or ARR was found in the available search results.

Competitive Landscape

Who it’s for, who it’s not for

Context.dev is aimed at developers building AI agents, LLM pipelines, research workflows, monitoring systems, and applications that need rendered web content or structured data without maintaining browsers, proxies, anti-bot systems, and site-specific extraction logic. [6gkbf3] [vrgqx2]
It is less suitable for teams seeking a self-hosted, open-source crawler or highly specialized scraping infrastructure that they want to control directly; the service uses a managed, usage-based API model rather than an open-source package model. [km4963] [60hucb]

Viable Alternatives

  • Scrapy: An open-source framework for teams that want direct control over crawl logic and infrastructure. [60hucb]
  • Browser automation stacks: Suitable when an application needs persistent, user-controlled browser sessions rather than stateless managed retrieval. [cmubd3]
  • Self-managed proxy and browser infrastructure: An alternative for organizations willing to operate rendering, proxy rotation, retries, and anti-bot systems themselves. [cmubd3]
  • Other managed scraping APIs: Viable where teams prioritize a different mix of rendering, extraction, crawling, pricing, or proxy capabilities; the available results do not establish a definitive market ranking.

Competitor Table

Competitor Description
Scrapy Open-source crawling framework that provides more infrastructure control but requires teams to manage rendering, retries, scheduling, and extraction components themselves. [60hucb]
Browser automation frameworks Tools for controlling browsers directly, useful for interactive or persistent sessions but requiring more operational infrastructure than Context.dev’s managed API. [l0qenp] [cmubd3]
Self-managed scraping stacks Internally operated combinations of browsers, proxies, anti-bot systems, and extraction code, offering customization at the cost of maintenance. [cmubd3]
Managed scraping APIs Commercial alternatives that provide some combination of rendering, proxying, crawling, and structured extraction; the available results do not identify a specific competitor with sufficient reliable detail.

Sources

Sources (retrieved)

[E1] Exa.ai API response for data on Context.dev (YC S26)