This open-source course teaches how to build modular, production-grade AI automation systems for enterprise use cases, focusing on a PR Reviewer integrated with GitHub, Slack, and Asana. It targets ML/AI, Software, and DevOps/MLOps engineers, enabling them to automate AI workflows, design scalable infrastructure, and evaluate Model Context Protocol (MCP) for enterprise migration.

How It Works

The series leverages the Model Context Protocol (MCP) to architect scalable AI automation. It details building custom MCP Servers for internal tools (Slack, Asana), integrating external MCP services (GitHub), centralizing resources in a global Tool Registry, and orchestrating complex workflows via a custom MCP Host. This modular, protocol-driven approach facilitates production-ready, enterprise-grade AI systems.

Quick Start & Requirements

Detailed setup instructions are available within the apps/pr-reviewer-mcp-host and apps/pr-reviewer-mcp-servers directories. Prerequisites include intermediate Python, beginner REST API/web development, and basic AI/LLM concepts. A modern PC is sufficient, as no GPU is required; all servers run locally or in containers. The course can be completed at zero cost using the Gemini free tier.

Highlighted Details

• Develop custom MCP Servers for Slack and Asana to expose enterprise tools.
• Integrate seamlessly with external MCP servers, such as GitHub Remote MCP.
• Establish an internal Tool Registry for centralized management of tools and prompts.
• Design and scale company-wide automation workflows using a custom MCP Host, avoiding reliance on external desktop applications.
• Implement a practical AI Pull Request Reviewer Assistant use case.

Maintenance & Community

This is an open-source course with core contributors Anca Ioana Muscalagiu and Paul Iusztin. Support and suggestions are managed via GitHub issues. Contributions, particularly bug fixes, are welcomed through pull requests, fostering community-driven development.

Licensing & Compatibility

The project is licensed under the permissive MIT License, allowing for broad compatibility, including commercial use and integration into closed-source applications.

Limitations & Caveats

As an open-source educational resource, the pace of bug resolution may depend on community contributions.