Jina Reader converts a web page into clean, LLM-friendly Markdown. Prepend r.jina.ai to a URL and the content comes back stripped of clutter, ready to ground a language model. Prepending s.jina.ai to a query performs a web search and returns the top five results in the same format. The service also reads images and PDFs, and an optional jina-ocr-v1 mode converts images into Markdown for pages and documents with complex structure, at a much higher token cost. An API key raises the rate limit.
Developers building retrieval pipelines, research agents and chat applications are the main users, since they need page text that models can read without scripts, ads and navigation. Prompt engineers and data teams can use the browser-style controls to target specific sections, and agent builders can connect through the MCP server. Hobbyists can try it by simply adding a prefix in a browser, with no setup, and teams needing higher throughput can add an API key.
Typical workflows include feeding documentation pages into a RAG index, giving an agent live web access, summarizing articles, extracting text from PDFs and captioning images so downstream models can reason about them. Request headers control output: choose a CSS selector to extract only the article body, wait for a dynamic element to load, remove navigation or footers, strip images to save tokens, add a links summary for navigation, set a token budget, forward cookies for authenticated pages or route through a country-specific proxy. A JSON response returns the URL, title, content and timestamp.
