Fashion Recommendation System
FastMCP_RecSys is a clothing recommendation system that uses CLIP (Contrastive Language-Image Pretraining) to analyze and classify fashion images. Built with a FastAPI backend and React frontend, it extracts clothing attributes like style, color, and fabric from uploaded images, then generates personalized recommendations based on detected tags and user behavior. The system stores clothing items and their metadata in MongoDB, making it particularly useful for e-commerce platforms seeking to enhance user experience through AI-powered fashion recommendations.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/attarmau/styleclip
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Fashion Recommendation System from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.