MCPHub LabRegistrymultimodal-agents-course
the-ai-merge

multimodal agents course

Built by the-ai-merge 552 stars

What is multimodal agents course?

An MCP Multimodal AI Agent with eyes and ears!

How to use multimodal agents course?

1. Install a compatible MCP client (like Claude Desktop). 2. Open your configuration settings. 3. Add multimodal agents course using the following command: npx @modelcontextprotocol/multimodal-agents-course 4. Restart the client and verify the new tools are active.
🛡️ Scoped (Restricted)
npx @modelcontextprotocol/multimodal-agents-course --scope restricted
🔓 Unrestricted Access
npx @modelcontextprotocol/multimodal-agents-course

Key Features

Native MCP Protocol Support
Real-time Tool Activation & Execution
Verified High-performance Implementation
Secure Resource & Context Handling

Optimized Use Cases

Extending AI models with custom local capabilities
Automating system workflows via natural language
Connecting external data sources to LLM context windows

multimodal agents course FAQ

Q

Is multimodal agents course safe?

Yes, multimodal agents course follows the standardized Model Context Protocol security patterns and only executes tools with explicit user-granted permissions.

Q

Is multimodal agents course up to date?

multimodal agents course is currently active in the registry with 552 stars on GitHub, indicating its reliability and community support.

Q

Are there any limits for multimodal agents course?

Usage limits depend on the specific implementation of the MCP server and your system resources. Refer to the official documentation below for technical details.

Official Documentation

View on GitHub
<h1 align="center">Kubrick Course</h1> <p align="center"> <img alt="logo" src="static/hal_9000.png" width=100 /> <h4 align="center" >Hi Dave...</h4> </p> <hr> <p align="center"> <h4 align="center">Learn to build AI Agents that can understand images, text, audio and videos.</h3> </p> <p align="center"> A <b>free, Open-source</b> course by <a href="https://theneuralmaze.substack.com"> The Neural Maze </a> and <a href="https://neuralbits.substack.com">Neural Bits</a> in collaboration with <a href="https://github.com/pixeltable">Pixeltable</a> and <a href="https://github.com/comet-ml/opik">Opik</a> </p> </br> <img alt="logo" src="kubrick-api/static/agent_architecture.gif" width=1000 /> </br>

📖 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 observability and prompt versioning

🖊️ What you'll learn

  • Learn how to use Pixeltable for multimodal data processing and stateful agents

  • Create complex MCP servers using FastMCP: expose resources, prompts, and tools

  • Apply prompt versioning to your MCP server (instead of defining the prompts in the Agent API)

  • Learn how to implement custom MCP clients for your agents

  • Implement an MCP Tool Agent from scratch, using Llama 4 Scout and Maverick as the LLMs

  • Use Opik for MCP prompt versioning

  • Learn how to implement custom tracing and monitoring with Opik

🚀 No shortcuts. No fluff. Let's learn by doing.


💻 What You'll Do:

Completing this course, you'll learn how to design and enable Agents to understand multimodal data, across images, video, audio, and text inputs, all within a single system.

Specifically, you'll get to:

  • Build a complex Multimodal Processing Pipeline
  • Build a Video Search Engine and expose its functionality to an Agent via MCP (Model Context Protocol)
  • Build a production-ready API to power the Agent.
  • Integrate LLMOps principles and best software engineering practices.
  • Learn about video, embeddings, streaming APIs, Vision Language Models (VLMs), and more.

After completing this course, you'll have built your own Kubrick Agent with a HAL-themed spin-off, to play the role of a new set of eyes and ears:

<video src="https://github.com/user-attachments/assets/ef77c2a9-1a77-4f14-b2dd-e759c3f6db72"/></video>


Getting Started

Kubrick is not a simple tutorial. So, to get this system up and running, there are a few things you need to do first.

We have detailed the steps to get you started in this GETTING_STARTED.md file.

💡 Having Kubrick running is just the first step! Now that you have it up and running, it's time to actually understand how it works (see Course Syllabus).


Watch the Full Video Course

<p align="center"> <a href="https://www.youtube.com/watch?v=_iYB1z1_Xgs&t=316s"><img src="static/video_thumbnail.png" alt="Kubrick Multimodal Agent" width="500"></a> </p>

🧑‍🎓 Who is this course for?

You'll get the most out of this course by building it yourself, from the ground up. The course components are structured to cover key concepts and demonstrate how to build upon them, ultimately leading to AI Systems.

Target AudienceSkills you'll get
ML/AI EngineersBuild complex MCP Servers, learn to apply AI Models to Video, Images, and Speech.
Software EngineersLearn to connect AI Components with APIs, building end-to-end agentic applications.
Data Engineers/ScientistsLearn to design an AI System, managing Video/Audio/Image data processing and structure.

Regardless of your experience or title, this course aims to unpack complex topics in practical terms and concepts you could understand, learn, and apply - helping you to build a complete AI system.

🎓 Prerequisites

In this section, we outlined a few requirements and nice-to-haves to improve your learning experience while taking this course.

CategoryLabelDescription
Programming Skills (Beginner)RequirementUnderstanding of Programming in general, and the Python language syntax.
AI/ML Concepts (Beginner)Nice to HaveUnderstanding the basic concepts behind AI, AI Models, and AI Systems.
LLMs, MCP, AgentsNice to HavePerfect if you know about them, not a problem if you don't. We'll teach and explain it step by step.
Laptop/PC with any OSRequirementAI Models inference requires compute. To overcome that, we'll mainly use API based models.

The overall level of this course is Beginner/Intermediate, but don't worry. We'll aim to explain every component step by step designed for a larger audience.

💰 What's the cost?

This course and its materials are open-source and completely free, thanks to our sponsors, Pixeltable and Opik!

You'll be able to run Kubrick examples while staying at a minimum cost. That's because we'll use OpenAI and Groq for our LLM and VLM calls, which offer freemium plans as such:

ProviderFree Credits
OpenAI$5 on first sign-up
Groq500,000 tokens/day

[!NOTE]
In this setup, for running the Kubrick Agent example, the freemium plans are enough.

📚 Course Syllabus

The Kubrick Agent open-source course consists of five comprehensive modules, covering concepts, system design, tooling, and hands-on implementation.

To get the most out of this course, we recommend:

  • Clone this repository.
  • Follow the Get Started Sections of each module.
  • Read the module articles to understand each component.
  • Follow the Video Lessons for hands-on implementation.
  • Set up the code and run the project.
Module No.In-depth Lesson (Link)Lesson Summary (3min)DescriptionCode
0<a href="https://multimodalai.substack.com/p/introducing-kubrick-course-a-multimodal"><img src="static/kubrick_ai_diagram.png" width=300></a>Get a SummaryCourse introduction and overview. Outlining the basic componentsN/A
1<a href="https://multimodalai.substack.com/p/cracking-the-code-of-multimodal-ai"><img src="kubrick-mcp/static/m2_mm_data_pipelines.png" width=300></a>Get a SummaryDiving into the core components of the multimodal processing pipeline, covering video, images, text, and audio data.kubrick-mcp
2<a href="https://multimodalai.substack.com/p/building-mcp-servers-for-video-search"><img src="kubrick-mcp/static/m2_mcp_servers_for_mm.png" width=300></a>Get a SummaryBuilding the Kubrick MCP Server with FastMCP. Covering MCP protocol (transport, communication), capabilities, tools, resources, and prompts. Adding Opik Integration and MCP Inspector for efficient debugging and local testing.kubrick-mcp
3<a href="https://multimodalai.substack.com/p/building-tool-use-mcp-agents-from"><img src="kubrick-api/static/m3_tooluse_agents.png" width=300></a>Get a SummaryBuilding the Kubrick MCP Agent from scratch. Memory layer implementation with Pixeltable and MCP Client with FastMCP. Understanding how to translate MCP Tools into specific provider tools (Groq)kubrick-api
4<a href="https://multimodalai.substack.com/p/building-a-fullstack-befe-agent-ui"><img src="kubrick-api/static/m4_building_agent_api.png" width=300></a>Get a SummaryBuilding the Groq Agent, covering the React UI - FastAPI API communication and adding LLMOps observability and conversation tracing with Opik (by Comet)kubrick-api
5<a href="https://multimodalai.substack.com/p/kubrick-course-final-round-up"><img src="kubrick-api/static/agent_architecture.gif" width=300></a>Get a SummaryComplete Round-up of the free, open-source Kubrick Course.N/A

Sponsors

<a href="https://www.pixeltable.com/" target="_blank"><img src="static/sponsors/pixeltable.png" width="250" alt="Pixeltable"></a><a href="https://github.com/comet-ml/opik" target="_blank"> <img src="static/sponsors/opik.png" width="250" alt="Opik"></a>
<p align="center">Pixeltable </br> is the only Python framework that provides incremental storage, transformation, indexing, and orchestration of your multimodal data.</p><p align="center">Opik </br>LLM Evaluation platform helps you build, evaluate, and optimize LLM systems that run better, faster, and cheaper</p>

Authors

<div align="center"> <table> <tr> <td align="center"> <a href="https://github.com/MichaelisTrofficus"> <img src="https://github.com/MichaelisTrofficus.png" width="100px;" alt="Miguel Otero Pedrido"/><br /> <sub><b>Miguel Otero Pedrido</b></sub> </a><br /> <sub>AI / ML Engineer</sub> <p> </br> <a href="https://linkedin.com/in/migueloteropedrido" target="_blank"> <img src="https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white" alt="LinkedIn"> </a> </p> </td> <td align="center"> <a href="https://github.com/arazvant"> <img src="https://github.com/arazvant.png" width="100px;" alt="Alex Razvant"/><br /> <sub><b>Alex Razvant</b></sub> </a><br /> <sub>AI / ML Engineer</sub> <p> </br> <a href="https://www.linkedin.com/in/arazvant" target="_blank"> <img src="https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white" alt="LinkedIn"> </a> </p> </td> </tr> </table> </div>

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PublicationDescriptionSubscribe
<a href="https://neuralbits.substack.com/" aria-label="Neural Bits"><img src="https://avatars.githubusercontent.com/u/114508542?s=400&u=abae5b0d28f288fc12502b170167a2ccce133f31&v=4" alt="Neural Bits Logo" width="100"/><br/><p align="center">Neural Bits</a></p>Learn about industry standards and production-ready AI Engineering.<a href="https://neuralbits.substack.com/"><img src="https://img.shields.io/static/v1?label&logo=substack&message=Subscribe%20Now&style=for-the-badge&color=black&scale=2" alt="Subscribe Now" height="30"></a>
<a href="https://theneuralmaze.substack.com/" aria-label="The Neural Maze"><img src="https://avatars.githubusercontent.com/u/151655127?s=400&u=2fff53e8c195ac155e5c8ee65c6ba683a72e655f&v=4" alt="The Neural Maze Logo" width="100"/><br/><p align="center">The Neural Maze</a> </a>Learn to build AI Systems that actually work, from principles to production. Delivered every Wednesday.<a href="https://theneuralmaze.substack.com/"><img src="https://img.shields.io/static/v1?label&logo=substack&message=Subscribe%20Now&style=for-the-badge&color=black&scale=2" alt="Subscribe Now" height="30"></a>

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Manual Config

{ "mcpServers": { "multimodal-agents-course": { "command": "npx", "args": ["multimodal-agents-course"] } } }