I have built bunch of MCP servers so far, and here is my take (and why I love it) There are 2 types of actions, (1) read-only and (2) MCP servers/tools with si

I have built bunch of MCP servers so far, and here is my take (and why I love it) There are 2 types of actions, (1) read-only and (2) MCP servers/tools with side effects 1. Read-only types. As you know, LLMs are static models, they don't learn things between your sessions, hence you need RAG or better prompting to enrich the context to get the best results for your use case. MCP helps you with enriching that context. For example, you want to categorize your recent emails, you can obviously copy paste all of them as a context, then ask LLM to categorize. Or you use MCP server to pull emails and add it to the context. This is very similar to RAG, but heavily personalized for your use case (e.g. by pulling data from Jira, Github only when you ask it) 2. MCPs with side effects (write/delete) - Here you can leverage NLP capabilities of MCP to take actions. For example, send email or create an event in your calendar, or enrich the contents of Jira ticket. Same as (1), you can ask LLM to come up with contents and then manually copy/paste it to your calendar to create an event or leverage the convenience of MCP tools to do it automatically. Here are some demos from my MCP servers: * Integration with Google Calendar to create events based on information of another MCP server (memory) - https://www.youtube.com/watch?v=ZgEy6Y1kfn4 https://www.youtube.com/watch?v=ZgEy6Y1kfn4 * Here you can see how easily you can integrate your OpenAPI based spec and use human language to query it - https://x.com/getaikoapp/status/1945278307496235482 https://x.com/getaikoapp/status/1945278307496235482