x-tweet-fetcher fetches tweets, lists, and articles from X/Twitter by employing smart backend routing. It addresses the limitations of X's API restrictions and the fragility of browser automation by utilizing Nitter for fast, dependency-free data and Playwright for comprehensive feature coverage. The project facilitates direct integration with AI agents by providing structured JSON output.
The project's key strength lies in its multi-backend approach, seamlessly switching between Nitter (for speed and simplicity), browser automation (for full features like lists and articles), and direct HTTP access for WeChat content. It seamlessly integrates with OpenClaw and Claude Code environments, and provides a self-hostable Nitter solution to overcome API limitations. The focus on structured JSON output simplifies integration into AI workflows.
- Backend Flexibility: Supports Nitter, Playwright (browser), and direct HTTP for diverse data retrieval methods.
- OpenClaw & Claude Code Compatibility: Designed for use in constrained environments, with native support for OpenClaw and easy integration with Claude Code.
- Self-Hosted Nitter: Provides instructions for setting up a private Nitter instance to overcome API limitations and rate limits.
- Structured JSON Output: All data is exported in JSON format for easy integration with AI agents and data processing pipelines.
- Comprehensive Capabilities: Fetches single tweets, replies, timelines, user profiles, lists, articles, and WeChat content.
The project is actively maintained with recent commits and documentation available. The development has a clear roadmap and a growing community. While reliance on public Nitter instances has risks, the project encourages self-hosting for reliable operation. The provided documentation allows for easy onboarding and use.
x-tweet-fetcher is valuable for researchers, analysts, and developers requiring access to X/Twitter data without relying on the X API or facing rate limiting issues. It offers a reliable and versatile solution for gathering and processing Twitter information for various applications, including AI agent development, social media analysis, and content monitoring. It simplifies data acquisition compared to manual scraping or fragile browser automation.