Today we're diving into one of the most important technologies in the AI ecosystem: Model Context Protocol (MCP).
If you've been wondering how AI models can securely interact with external systems like GitHub, AWS, databases, Kubernetes, or other DevOps tools, MCP is the answer.
In today's video, we cover:
✅ What is MCP and why it matters
✅ How MCP works behind the scenes
✅ Setting up and using the GitHub MCP Server
✅ Connecting to the AWS MCP Server
✅ Real-world DevOps use cases for MCP
I'm also happy to share that DevOps Open Agent supports MCP. 🎉
🔗 https://github.com/ideaweaver-ai/devops-open-agent
🎥 https://youtu.be/9HjWLyoHdng
With MCP support, DevOps Open Agent can connect to external MCP servers and use them as tools, making it easier to investigate infrastructure, interact with GitHub repositories, access cloud resources, and integrate with the growing MCP ecosystem.
As more platforms adopt MCP, this becomes a powerful way to extend AI agents without building custom integrations for every service.
🔗 Day 10 (English): https://www.ideaweaver.ai/courses/100-days-of-genai-for-devops-english/lectures/66317915
🔗 Day 10(Hindi): https://www.ideaweaver.ai/courses/100-days-of-genai-for-devops-hindi/lectures/66317916
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