Initialize AI Infrastructure Module with MCP Submodule

[kevinevans1]

As a
platform engineer at Code to Cloud,

I want
to create a structured, documentation-first AI Infrastructure module with an initial focus on Model Context Protocols (MCP),

So that
we can define the foundation for scalable, context-aware AI systems and guide future Terraform-based implementation with clarity and consistency.

⸻

✅ Acceptance Criteria
• A new /ai-infra/ directory is created in the repo with a top-level README.md that:
• Introduces the purpose of AI Infrastructure within Code to Cloud
• Lists guiding principles (modularity, context-awareness, Terraform-first, Azure-native)
• Defines planned submodules (MCP, memory, agents, runtime)
• A subdirectory /ai-infra/mcp/ is created with its own README.md that:
• Explains the purpose of Model Context Protocols in multi-agent and LLM workflows
• Lists key infrastructure components that will support MCPs (e.g., Azure OpenAI, Key Vault, Storage)
• Includes references to Microsoft Docs, Terraform modules, and patterns from LangChain, LangGraph, or AutoGen
• Is written for clarity and extensibility — as a staging area for future code

🧠 Notes
• This is a documentation-first milestone: no infrastructure or code is being provisioned yet.
• This will act as a foundational artifact to onboard contributors and align future infrastructure development.
• MCP is chosen as the first submodule because it’s the core protocol for managing model context and agent interaction across the system.