Which is more popular, Taxy AI or Firecrawl?

Firecrawl has more GitHub stars (188,094 vs 1,278).

Which is more actively developed, Taxy AI or Firecrawl?

Firecrawl had more commits in the last 90 days (600 vs 0).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

Taxy AI has had no commit in 20 months; Firecrawl is actively maintained (600 commits in the last 90 days).
Firecrawl is growing faster: +14,035 GitHub stars in the last 30 days vs +1 for Taxy AI.
Pick Taxy AI for: automate your browser with GPT-4. Pick Firecrawl for: the Web Data API for AI - Turn entire websites into LLM-ready markdown or structured data.

From GitHub data refreshed daily.

Taxy AIopen-source

Automate your browser with GPT-4

🔥 The Web Data API for AI - Turn entire websites into LLM-ready markdown or structured data

+Industry-leading reliability with >80% success rate on complex websites including JavaScript-heavy and dynamic content
+AI-optimized output formats with clean markdown and structured data specifically designed for LLM consumption
+Comprehensive feature set including media parsing, interactive actions, batch processing, and authentication support

-Repository is still in development and not fully ready for self-hosted deployment
-API-based service likely requires subscription pricing for production use
-As a relatively new tool, long-term stability and support ecosystem may be uncertain

•Building AI agents that need real-time web context and competitor intelligence
•Creating training datasets for LLMs by scraping and cleaning large volumes of web content
•Automating content monitoring and change detection for business intelligence applications

Which is more popular, Taxy AI or Firecrawl?: Firecrawl has more GitHub stars (188,094 vs 1,278).
Which is more actively developed, Taxy AI or Firecrawl?: Firecrawl had more commits in the last 90 days (600 vs 0).
Should I use Taxy AI or Firecrawl?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.