by the-ai-merge · MCP Server · ★ 576
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Kubrick Course Hi Dave... Learn to build AI Agents that can understand images, text, audio and videos. A free, Open-source course by The Neural Maze and Neural Bits in collaboration with Pixeltable and Opik 📖 About This Course Tired of tutorials that just walk you through connecting an existing MCP server to Claude Desktop? Yeah, us too. That's why we built Kubrick AI, an MCP Multimodal Agent for video processing tasks. Yes! You read that right. 💡 Agents + Video Processing ... and MCP! This course is a collaboration between The Neural Maze and Neural Bits (from now on, "The Neural Bros"), and it's built for developers who want to go beyond the basics and build serious, production-ready AI Systems. In particular, you'll: Learn how to build an MCP server for video processing using Pixeltable and FastMCP Design a custom, Groq-powered agent, connected to your MCP server with its own MCP client Integrate your agentic system with Opik for full observabilit
| Stars | 576 |
| Forks | 148 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 57.9549549148915/100 |
| Open Issues | 2 |
| Last Updated | 2026-01-05 |
| Created | 2025-04-07 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~6807k |
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multimodal-agents-course is An MCP Multimodal AI Agent with eyes and ears!. It is categorized as a MCP Server with 576 GitHub stars.
multimodal-agents-course is primarily written in Python. It covers topics such as agent, embeddings, groq.
You can find installation instructions and usage details in the multimodal-agents-course GitHub repository at github.com/the-ai-merge/multimodal-agents-course. The project has 576 stars and 148 forks, indicating an active community.
multimodal-agents-course is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to multimodal-agents-course on Agent Skills Hub include paperdebugger, better-chatbot, MakerAi. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.