AI Tools Scout tracks the AI builder ecosystem: open-source projects, MCP servers, AI skills, and technical content. The goal is to help developers evaluate adoption, momentum, and maintenance signals before committing time to a tool.
The site focuses on developer-facing AI infrastructure rather than generic SaaS directories. Project pages emphasize GitHub health signals, MCP pages emphasize connectivity and deployment context, skills pages cover reusable agent capabilities, and the content hub surfaces tutorials, research, and AI news.
Sync cadence depends on the active deployment setup. Directory pages show their latest observed sync time so time-sensitive rankings can be checked directly.
Every tracked project receives a health score from 0 to 100, computed from weighted maintenance and adoption signals. The score is a screening tool, not a replacement for reviewing the repository, license, and issue history yourself.
| Signal | Weight |
|---|---|
| Star growth momentum | 20% |
| Commit frequency | 20% |
| Issue response health | 15% |
| Contributor diversity | 15% |
| Release cadence | 10% |
| Documentation quality | 10% |
| Community signal | 10% |
Project metrics come from GitHub REST and GraphQL APIs. MCP data is aggregated from public registries and curated lists. Skills and content come from public ecosystem sources, package metadata, RSS feeds, YouTube feeds, Hacker News, and selected AI communities where available.
Have feedback or want to suggest a project? Open an issue on GitHub.