Cursor vs mlc-ai

Cursor and mlc-ai both appear on the Smoower Developer Ecosystem Index.

mlc-ai (rank #209) holds a modest lead over Cursor (rank #430) on the overall Smoower ecosystem score (49 vs 40). The gap of 9 points reflects composite signals across code, docs, community and reach.

On code quality (the state of repositories, tests, releases and polish), mlc-ai is clearly ahead of Cursor. On education (docs, guides and learning material for developers), mlc-ai is clearly ahead of Cursor. On community (issue response, PR reviews and discussion health), mlc-ai is ahead of Cursor. On reach (how visible the ecosystem is beyond its own repos), Cursor is clearly ahead of mlc-ai. On momentum (release cadence and how fast the ecosystem moves), Cursor is slightly ahead of mlc-ai.

Cursor carries 44,397 GitHub stars across 8 public repos, with 5 repositories active in the last 90 days and 41 external contributors on record. mlc-ai shows 51,532 stars across 38 public repos, 15 active in the last 90 days and 45 external contributors.

Cursor is the stronger read for anyone weighting reach. mlc-ai looks better where education 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.