Context.dev

Product Introduction

1. Definition: Context.dev is a comprehensive, unified web context API platform designed for developers building AI products, agents, and data-driven applications. It technically functions as a managed data pipeline, combining web scraping, crawling, structured data extraction, and brand intelligence into a single RESTful API.
2. Core Value Proposition: It exists to eliminate the infrastructure burden of sourcing live, structured web data. Instead of building and maintaining internal scrapers, combining multiple vendors, or relying on stale LLM knowledge, developers can use Context.dev's single API to power features like AI agent context, RAG grounding, automated onboarding, and company enrichment with real-time web data.

Main Features

1. Web Scraping & Crawling API: This feature provides clean, LLM-ready Markdown and rendered HTML from any URL. It works by deploying headless browsers to execute JavaScript and render dynamic content, then extracting and cleaning the textual content. It supports single URL scraping, full-site crawling based on sitemaps or discovery, and image extraction. Specific technologies include distributed crawling infrastructure and anti-blocking mechanisms to ensure high success rates.
2. Structured Data Extraction via JSON Schema: This AI-powered feature allows users to define a precise Zod or JSON schema and extract matching structured data from any webpage. How it works: The system first fetches and renders the page, then uses a fine-tuned LLM model to identify and map relevant information on the page to the user-defined schema fields, outputting validated JSON. This replaces manual parsing and brittle regex.
3. Brand Intelligence API: This feature resolves a domain, email, or company name into a typed company profile. It works by crawling the target website and analyzing its HTML, CSS, and metadata to extract logos (with a dedicated CDN), color palettes, fonts, style guides, social media links, descriptions, addresses, and firmographic data like industry codes (NAICS/SIC). The technology involves computer vision for logo detection and CSS parsing for design system extraction.
4. Logo Link CDN: A separate, high-performance service that delivers a company's square logo via a simple, cacheable image URL. It works by providing a direct img tag source (e.g., https://logos.context.dev?domain=example.com) that serves optimized logos from a global content delivery network with ~20ms latency, independent of the main API credit system.
5. Transaction Identification: This feature parses messy transaction descriptors from bank or credit card statements (e.g., "SQ *BLUE BOTTLE 8xx") and identifies the underlying brand. It works by using a combination of fuzzy matching, merchant category code (MCC) hints, and location data to map the string to a known company in Context.dev's database, enriching it with the brand's visual and metadata.

Problems Solved

1. Pain Point: Data Infrastructure Overhead. Building and maintaining reliable web scrapers, crawlers, and data pipelines is a complex, time-consuming engineering task that distracts from core product development.
2. Pain Point: Fragmented Vendor Stack. Product teams often need to use separate services for scraping, brand logos, company data, and screenshots, leading to integration complexity and higher costs.
3. Pain Point: Stale or Unstructured Data for AI. LLMs and AI agents are often limited by their training cut-off date and lack real-time web context, while RAG systems are fed with poorly parsed, unstructured HTML.
4. Target Audience: AI/ML Engineers and Developers building LLM-powered agents, chatbots, and copilots that require live web knowledge. Product Managers and Developers needing to autofill onboarding forms, enrich user profiles, or theme UIs programmatically with brand data. Data Engineers requiring reliable, scheduled web data extraction pipelines without managing proxies or anti-bot systems.
5. Use Cases: Grounding RAG Pipelines: Automatically crawl a documentation site's sitemap, convert all pages to clean Markdown, and embed them to keep a knowledge base current. Autofilling Onboarding: Use a user's work email domain to pre-populate company name, logo, and brand colors during signup, reducing friction. Powering AI Agents: Give an autonomous agent the ability to GET /v1/scrape/markdown for any URL to reason over live information. Enhancing CRM Data: Enrich lead or company records with logos, social links, and descriptions pulled directly from their website.

Unique Advantages

1. Differentiation: Unlike generic scraping APIs (e.g., ScrapingBee, ScrapingBot) or pure web crawlers (e.g., Firecrawl), Context.dev bundles brand intelligence, structured extraction, and web scraping into one cohesive platform. Unlike traditional business data APIs, it extracts data directly from the live web rather than relying on potentially outdated databases. Its Logo Link CDN offers a uniquely simple and performant solution for frontend logo display.
2. Key Innovation: The "Agentic Setup" and dedicated auth.md endpoint represent a novel approach to developer onboarding tailored for the age of AI coding assistants, allowing an AI agent to sign up and integrate the API autonomously. Furthermore, its schema-based extraction uses AI not just for generic parsing but for guaranteed JSON output matching a user-defined structure, bridging the gap between unstructured web data and application databases.

Frequently Asked Questions (FAQ)

1. What is the difference between Context.dev's API credits and Logo Link service? API credits are consumed for programmatic calls to the web scraping, brand data, and extraction endpoints (1 credit for web calls, 10 for brand calls). Logo Link is a separate, rate-limit-free service that provides a direct image URL for embedding logos in a frontend; its requests have a separate quota and do not consume API credits.
2. How does Context.dev handle JavaScript-heavy websites like React or Vue.js applications? The web scraping API uses a headless browser rendering engine to fully execute JavaScript, wait for page loads, and extract the fully-rendered DOM content, ensuring accurate data extraction from modern single-page applications (SPAs).
3. Is there a free tier for the Context.dev API, and what are the limits? Yes. Signing up with a work email grants 500 API credits (at 30 requests/minute) and 10,000 Logo Link requests per month. Using a free email provider (Gmail, etc.) provides 250 API credits (at 10 requests/minute). This allows for testing core functionalities like scraping and brand lookup.
4. How current is the brand data provided by Context.dev's API? Cached brand data is automatically refreshed every quarter. When an API request is made for data older than 3 months, the system triggers a fresh crawl. Users can also manually request an immediate update for a specific domain via a dedicated brand update form.
5. Can I use Context.dev for large-scale, scheduled crawling of an entire website? Yes. The platform supports full-site crawling via sitemap discovery or recursive crawling. This is designed for use cases like building or updating a RAG knowledge base. Users on Scale or Enterprise plans are equipped for high-volume, scheduled crawling operations.