Quetre

Quetre is an open-source, libre front-end for Quora that proxies Quora pages to provide an ad-free, tracker-free reading experience. It also offers an unofficial JSON API endpoint for programmatic access (api/v1).

Key Features

• Privacy-focused proxying of Quora requests to avoid Quora-side tracking and telemetry
• No ads, no trackers, no browser fingerprinting or telemetry collected by the front-end
• Lightweight, responsive site built with Pug templates and Sass-based styling for dark/light themes
• Unofficial JSON API (add /api/v1/ to an instance) for programmatic access to parsed content
• Optional Redis caching support and Docker-friendly deployment artifacts (docker-compose/service files)
• Simple installation and run scripts driven by pnpm / Node.js and a small set of dependencies (Express, axios, cheerio, pug, sass, dotenv)

Use Cases

• Privacy-conscious browsing of Quora content without ads or tracking, useful for individuals and privacy-focused communities
• Hosting a public or private instance that serves as a lightweight alternative front-end for embedding or redirects
• Providing a parsed JSON endpoint for tooling, redirectors, or integration with browser extensions that replace Quora URLs

Limitations and Considerations

• Not all Quora routes are implemented; some pages or answers may be unreachable due to Quora's dynamic loading and unique IDs, and the project lists missing routes in its TODOs
• Getting all answers on some pages can be difficult because Quora loads additional answers via client-side requests; Quetre may not fetch every dynamically loaded item
• Math rendering relies on MathJax in the browser; with JavaScript disabled math may display improperly
• There is no account system or user-authentication integration; interactive Quora features (voting, posting, private content) are not provided

Quetre is a compact, privacy-oriented option for reading Quora content and exposing a simple parsed API. It is implemented as a small Node.js/Express application with templating and styling focused on a fast, minimal user experience.