Great breakdown of the MCP architecture! The STDIO vs SSE distinction is particularly important - STDIO for local integrations keeps latency minimal, while SSE enables remote server composition.
What's fascinating about MCP is how it shifts agent development from "build integrations" to "configure protocol clients." The Docker Hub MCP registry (hub.docker.com/u/mcp) is essentially becoming a package manager for agent capabilities.
One thing I'd add: the inputSchema pattern MCP uses mirrors what we're seeing in production agent frameworks. OpenAI's function calling, Anthropic's tool definitions, and now MCP all converged on JSON Schema for describing tool interfaces. That's not accidental - it's the contract layer that makes tools swappable across models.
Looking forward to your follow-up on building custom MCP servers. The real unlock will be when we get MCP servers that compose other MCP servers - tools calling tools across protocol boundaries.
Thanks for the Ollama example too - local-first agent development is the direction things are heading, and having MCP work with local LLMs removes a key friction point.