{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/de559bb0aef749559c79117b7f951250\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/de559bb0aef749559c79117b7f951250-1cf817707a1862dc.gif","duration":1361.773,"title":"Unlocking the Power of TraceMind MCP Server for AI Optimization 🚀","description":"Hello everyone, I'm Kshitij from Mumbai India, and in this video, I introduced our TraceMind MCP server, designed to analyze real agent evaluation datasets for businesses looking to implement Gen AI. I discussed how our ecosystem addresses the need for deeper insights beyond standard leaderboards, allowing users to optimize models and improve performance. I showcased our four projects, including TraceVerde, a no-code instrumentation framework, and SmolTrace, an evaluation framework that generates custom datasets. I demonstrated the MCP server's capabilities, including analyzing leaderboards and estimating costs, and I encourage you to check out the TraceMind AI UI for more insights. If you find the MCP server useful, please give it a like!"}