Web data API for AI
Firecrawl vs Mage
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Firecrawl (Web data API for AI) and Mage (Magical tools for data.) both appear on the Smoower Developer Ecosystem Index.
Firecrawl (rank #122) holds a modest lead over Mage (rank #485) on the overall Smoower ecosystem score (54 vs 38). The gap of 16 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Firecrawl is ahead of Mage. On education (docs, guides and learning material for developers), Firecrawl is ahead of Mage. On community (issue response, PR reviews and discussion health), Firecrawl is ahead of Mage. On reach (how visible the ecosystem is beyond its own repos), Mage is ahead of Firecrawl. On momentum (release cadence and how fast the ecosystem moves), Firecrawl is clearly ahead of Mage.
Firecrawl carries 199,181 GitHub stars across 101 public repos, with 28 repositories active in the last 90 days and 130 external contributors on record. Mage shows 9,079 stars across 44 public repos, 8 active in the last 90 days and 22 external contributors. The star gap on its own does not decide the comparison, but Firecrawl's footprint is roughly 21.9x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
Firecrawl is the stronger read for anyone weighting momentum. Mage looks better where reach is the deciding factor. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.
Side-by-side metrics
| Metric | Firecrawl | Mage |
|---|---|---|
| Ranking | ||
| Overall rank | #122 | #485 |
| Pillars | ||
| Overall | 54 | 38 |
| Code | 48 | 34 |
| Education | 87 | 71 |
| Community | 52 | 38 |
| Reach | 27 | 40 |
| Momentum | 37 | 16 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 199,181 | 9,079 |
| Forks | 17,907 | 1,538 |
| Public repos | 101 | 44 |
| Active repos (90d) | 28 | 8 |
| External contributors | 130 | 22 |
| Avg polish | 48 | 42 |
| Avg AI-readiness | 39 | 15 |